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> Physiology > Genetic Function > Loss of Function Mutation

Loss of Function Mutation

Loss of function mutations are genetic variations that result in the reduced or absen activity of a gene product.
These mutations can have significant impacts on biological processes and are linked to a variety of human diseases.
Researchers studying loss of function mutations rely on robust experimental protocols to ensure reproducibility and advance their understanding of these important genetic changes.
PubCompare.ai helps scientists optimize their research by identifying the most reliable and effective protocols from the published literature, preprints, and patent data.
Our AI-driven comparisons provide an easy way to locate the best approaches for your loss of function mutation studies and accelerate your scientific discovery.

Most cited protocols related to «Loss of Function Mutation»

1
Identifying Breast Cancer Driver Genes
To identify genes that may be relevant to breast cancer, we looked for those that harboured multiple recurrent or inactivating mutations, as these are mutation patterns typical of oncogenes and tumour suppressors. Recurrent mutations were defined as missense SNVs and in-frame substitutions that affected the same codon of the annotation transcript, whereas inactivating mutations included nonsense SNVs, frameshift substitutions and variants that affected splice sites. The proportions of recurrent (ONC) and inactivating (TSG) mutations for each gene (out of the total number of mutations) were computed, and a threshold of 0.2 was used (20/20 rule). Genes with an ONC score >0.2 and with a TSG score >0.05 were classified as tumour suppressors. A minimum of five recurrent or inactivating mutations was required for a gene to be selected as putative drivers. The method was adapted from the study by Vogelstein et al.16 (link)
Pereira B., Chin S.F., Rueda O.M., Vollan H.K., Provenzano E., Bardwell H.A., Pugh M., Jones L., Russell R., Sammut S.J., Tsui D.W., Liu B., Dawson S.J., Abraham J., Northen H., Peden J.F., Mukherjee A., Turashvili G., Green A.R., McKinney S., Oloumi A., Shah S., Rosenfeld N., Murphy L., Bentley D.R., Ellis I.O., Purushotham A., Pinder S.E., Børresen-Dale A.L., Earl H.M., Pharoah P.D., Ross M.T., Aparicio S, & Caldas C. (2016). The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nature Communications, 7, 11479.
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Publication 2016
Codon Frameshift Mutation Genes Loss of Function Mutation Malignant Neoplasm of Breast Mutation Mutation, Nonsense Oncogenes Reading Frames Tumor Suppressor Genes
2
Pathway Alteration Frequency Analysis

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Publication 2010
Androgens Diploid Cell Down-Regulation Gain of Function Mutation Genes Genetic Selection Lanugo Loss of Function Mutation Missense Mutation Mutation Neoplasms Prostate Student TIF2 factor, human
3
Predicting Tumor Suppressors and Oncogenes

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Publication 2013
6H,8H-3,4-dihydropyrimido(4,5-c)(1,2)oxazin-7-one Entropy Frameshift Mutation Gene, Cancer Genes Loss of Function Mutation Missense Mutation Mutation Mutation, Nonsense
4
Identifying Significantly Mutated Genes in Cancer
Significantly mutated genes were identified using MutSig2CV which combines p-values from tests for high mutational frequency relative to the background mutation rate (pCV), clustering of mutations within the gene (pCL), and enrichment of mutations within evolutionarily conserved sites (pFN)10 (link). For 660 lung adenocarcinomas, we had 100% power to detect genes mutated in 10% of patients and 73% power for genes mutated in 5% of patients assuming a mutation rate of 8.7/Mb10 (link). For 484 lung squamous cell carcinomas, we had 100% power to detect genes mutated in 10% of patients and 41% power for genes mutated in 5% of patients assuming a mutation rate of 9.7/Mb10 (link). In order to reduce the number of hypotheses tested in the MutSig2CV analysis, we excluded genes that exhibited low expression across tumors with relatively high purity. The median log2 FPKM value for each gene was obtained for 185 ADCs or 238 SqCCs which had a purity estimate from ABSOLUTE of >50% and available RNA-seq data (Supplementary Fig. 1). For each tumor type, a mixture model of two normal distributions was fit in R using the mclust package v4.2. Genes with 95% probability of belonging to the cluster with higher expression were considered in the multiple hypothesis correction of the MutSig2CV combined p-values. One gene, TRERF1, was excluded from the final results as closer inspection of its mutations revealed a recurrent frameshift deletion that was likely a false positive as all of these mutations had low allelic fractions (<1.5%) and had no supporting reads in matching RNA-seq data. A one-sided Fisher’s exact test was used to determine if the proportion of loss-of-function mutations (including nonsense, frameshift, and de novo start out-of-frame mutations) to other mutations for a given gene was significantly higher compared to the proportion of loss-of-function mutations to other mutations across all other genes.
Campbell J.D., Alexandrov A., Kim J., Wala J., Berger A.H., Pedamallu C.S., Shukla S.A., Guo G., Brooks A.N., Murray B.A., Imielinski M., Hu X., Ling S., Akbani R., Rosenberg M., Cibulskis C., Ramachandran A., Collisson E.A., Kwiatkowski D.J., Lawrence M.S., Weinstein J.N., Verhaak R.G., Wu C.J., Hammerman P.S., Cherniack A.D., Getz G., Artyomov M.N., Schreiber R., Govindan R, & Meyerson M. (2016). Distinct patterns of somatic genome alterations in lung adenocarcinomas and squamous cell carcinomas. Nature genetics, 48(6), 607-616.
Publication 2016
Adenocarcinoma of Lung Alleles Deletion Mutation Frameshift Mutation Genes Loss of Function Mutation Lung Mutation Mutation, Nonsense Neoplasms Patients RNA-Seq Squamous Cell Carcinoma TRERF1 protein, human
5
Genetically Engineered Mouse Model for IDH1 Glioma
To study the impact of IDH1R123H activity in the contex of TP53 and ATRXKD, we generated a genetically ingieneered animal model injecting Sleeping Beauty plasmids encoding NRAS-G12V, shp53, with or without shATRX, and with or without IDH1R132H into the lateral ventricle of neonatal mice. Sample size and any data inclusion/exclusion were defined individually for each experiment. In addition, we used an intracranial animal model generated by implantation of glioma NS (wt-IDH1 and mIDH1) derived from our genetically ingieneered animal model to test theraupeutic responses. We also used an alternative model (PDGFB/shP53/shATRX/Ink4a/Arf-/- wtIDH1 or mIDH1 NS) which does not encode RAS activating mutations. We also used human glioma cells derived from patients harboring IDH1R132H in the context of TP53 and ATRX inactivating mutations, to confirm the results obtained from our animal models. Number of replicates are reported in the figure legends. Our studies were not randomized. We performed blinding for quantitative immunohistochemistry scoring. All RNA-seq and ChIP-seq data was deposited in public data-bases as is indicated in the respective sections. Material and methods are detailed in supplementary materials section.
Núñez F.J., Mendez F.M., Kadiyala P., Alghamri M.S., Savelieff M.G., Garcia-Fabiani M.B., Haase S., Koschmann C., Calinescu A.A., Kamran N., Patel R., Carney S., Guo M.Z., Edwards M., Ljungman M., Qin T., Sartor M.A., Tagett R., Venneti S., Brosnan-Cashman J., Meeker A., Gorbunova V., Zhao L., Kremer D.M., Zhang L., Lyssiotis C.A., Jones L., Herting C.J., Ross J.L., Hambardzumyan D., Hervey-Jumper S., Figueroa M.E., Lowenstein P.R, & Castro M.G. (2019). IDH1-R132H acts as a tumor suppressor in glioma via epigenetic upregulation of the DNA damage response. Science translational medicine, 11(479), eaaq1427.
Publication 2019
Alpha Thalassemia X-Linked Intellectual Disability Syndrome Animal Model CDKN2A Gene Cells Chromatin Immunoprecipitation Sequencing Gain of Function Mutation Glioma Homo sapiens Immunohistochemistry Infant, Newborn Loss of Function Mutation Mice, Laboratory NRAS protein, human Ovum Implantation Patients PDGFB Gene Plasmids RNA-Seq TP53 protein, human Ventricle, Lateral

Most recents protocols related to «Loss of Function Mutation»

1
Generating Prdm16-Lux Reporter in Human Cells
The CAGA9-Lux gene reporter construct was previously described (Seo et al., 2006 (link)). The expression vector pcDNA3.1-Prdm16 was a gift from Dr. Bruce Spiegelman (#15503; Addgene). The expression vector pCMV5-HA-Smad4 was a gift from Dr. Joan Massague. To generate the Prdm16-Lux reporter, genomic fragments (1,391 bp) upstream of the transcription initiation site (SST) of the PRDM16 gene (based on gene association NM_022114 and Eukaryotic Promoter Database, epd.epfl.ch) was amplified by the Genomic-GC PCR amplification kit (BD Biosciences) using human genomic DNA obtained from PANC-1 cells. Unique KpnI and XhoI sites were incorporated at the 5′ and 3′ ends of the sequence, respectively, to simplify directional cloning into KpnI and XhoI sites in the reporter plasmid, pGL3-basic (Promega). Introduction of inactivating mutation into the SBE sequence (−41 bp from SST) was generated by PCR using the QuickChange Site-Directed Mutagenesis kit according to the manufacturer’s instructions (Stratagene). The lentiCRISPRV2 expression vectors encoding SMAD4 and PRDM16 gRNAs were purchased from GenScript. The lentiCRISPRV2 expression vectors encoding SMAD2 and SMAD3 gRNAs were generated using lentiCRISPRV2 hygro (#98291; Addgene) and primers with sequences generated using the Synthego Design tool. All cloned cDNAs and their corresponding mutants were checked by sequencing.
Hurwitz E., Parajuli P., Ozkan S., Prunier C., Nguyen T.L., Campbell D., Friend C., Bryan A.A., Lu T.X., Smith S.C., Razzaque M.S., Xu K, & Atfi A. (2023). Antagonism between Prdm16 and Smad4 specifies the trajectory and progression of pancreatic cancer. The Journal of Cell Biology, 222(4), e202203036.
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Publication 2023
Cells Cloning Vectors DNA, Complementary Eukaryota Genes Genome Genome, Human Loss of Function Mutation MEL1S protein, human Mutagenesis, Site-Directed Oligonucleotide Primers Paragangliomas 3 Plasmids Promega SMAD2 protein, human SMAD3 protein, human SMAD4 protein, human Transcription Initiation Site
2
Chikungunya and Venezuelan Equine Encephalitis Virus Constructs
All oligonucleotide sequences used are listed in S3 Table. All constructs were verified by sequence analysis. IRES-eGFP was amplified from pL-eGFP, a plasmid with a T7 promoter in which the foreign gene is under control of an encephalomyocarditis virus internal ribosomal entry site and inserted in plasmid pCAGGS/MCSII [104 (link)] using XhoI and BglII restriction sites using standard cloning techniques to create pCAGGS-IRES-GFP. The nucleotide sequences of CHIKV nsPs and protein domains were amplified from pCHIKV-LS3 [21 (link)] and pCHIKrepLS3-nCPE, a replicon derivative from pCHIKV-LS3 mutated in nsP2 (P718S, K649D and R650H), and inserted into pCAGGS-IRES-GFP using EcoRI or SacI and XhoI. Firefly luciferase was amplified from pGL3-MKP-1-Luc [105 (link)] and inserted into pCAGGS-IRES-GFP using EcoRI and XhoI.
pCAGGS-VEEV-nsP2-NTD-Hel was created by amplifying the nsP2-NTD-Hel sequence from cDNA prepared from the VEEV TC-83 stock. The PCR oligonucleotides introduced a start codon, N-terminal HA-tag, a stop codon and SacI and XhoI restriction sites to use for cloning.
pCAGGS-CHIKV-nsP2-NTD-Hel and pCAGGS-VEEV-nsP2-NTD-Hel Walker A and B mutants were created by cloning the CHIKV-nsP2-NTD-Hel or VEEV-nsP2-NTD-Hel PCR product into pCR2.1-TOPO (Thermo Fisher Scientific) for site-directed mutagenesis to introduce the Walker A and B-inactivating mutations prior to transferring the mutated sequences to pCAGGS-IRES-GFP. Renilla luciferase was expressed from phRL-TK or pRL-TK (both Promega).
pCAGGS-FLAG-eEF2 was created by cloning the human synthetic FLAG-eEF2 (IDT) sequence into pCAGGS-MCSII [104 (link)]. pCMV-FLAG-Ub expressed FLAG-tagged ubiquitin [106 (link)]. pCDNA3-FLAG-UbcH10 was a kind gift from prof. Akira Nakagawara (Chiba Cancer Centre, Japan) [107 (link)].
Treffers E.E., Tas A., Scholte F.E., de Ru A.H., Snijder E.J., van Veelen P.A, & van Hemert M.J. (2023). The alphavirus nonstructural protein 2 NTPase induces a host translational shut-off through phosphorylation of eEF2 via cAMP-PKA-eEF2K signaling. PLOS Pathogens, 19(2), e1011179.
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Publication 2023
Base Sequence Codon, Initiator Codon, Terminator Deoxyribonuclease EcoRI DNA, Complementary DUSP1 protein, human Encephalomyocarditis virus Genes Homo sapiens Internal Ribosome Entry Sites Loss of Function Mutation Luciferases, Firefly Luciferases, Renilla Malignant Neoplasms Mutagenesis, Site-Directed Oligonucleotides Paragangliomas 3 Plasmids Promega Protein Domain Replicon Sequence Analysis Topotecan UBE2C protein, human Ubiquitin Walkers
3
Generating CRISPR Knockout Cell Line
CRISPR vectors were constructed using the GeneArt CRISPR Nuclease (OFP Reporter) Vector Kit (Invitrogen). NOP12 cells were transfected with the CRISPR Nuclease Vector containing the insert AGGACGAGAGGCCGTTCCCC, using Lipofectamine 3000. Four days later, cells were sorted for OFP expression and single cells were plated by limiting dilution. Colonies were screened using a BD Cytometric Bead Array for GCSF (Beckton-Dickinson). Sanger sequencing revealed a loss-of-function (LOF) mutation in nucleotide 33 within exon 2 of the murine csf3 gene.
Matos I., Barvalia M., Chehal M.K., Robertson A.G., Kulic I., Silva J.A., Ranganathan A., Short A., Huang Y.H., Long E., Priatel J.J., Dhanji S., Nelson B.H., Krebs D.L, & Harder K.W. (2023). Tumor-derived GCSF Alters Tumor and Systemic Immune System Cell Subset Composition and Signaling. Cancer Research Communications, 3(3), 404-419.
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Publication 2023
Cells Cloning Vectors Clustered Regularly Interspaced Short Palindromic Repeats Exons Genes Granulocyte Colony-Stimulating Factor Lipofectamine Loss of Function Mutation Mus Nucleotides Technique, Dilution
4
Rare Genetic Variant Identification Pipeline
The peripheral blood was collected from the probands, their parents and other available family members to determine the origin of the identified genetic variants. Genomic DNA (>3 μg) was extracted using the DNA mini kit (Aidlab Biotech, China). The kinship of four trios’ samples have been checked, and the data is shown in Supplementary Table 1 and novel variants identified in this study were submitted to ClinVar (SCV002817420- SCV002817422). Sequencing reads were aligned to the reference human genome (GRCh37/hg19) using the BWA2 (v0.7.15). Picard was applied to sort by chromosome coordinates and mark duplicates1. Single nucleotide variants and insertions/deletions of samples were called and the Variant Call Format (VCF) file was generated (format v4.1) by HaplotypeCaller v4.0 from Genome Analysis Toolkit (GATK) (Van der Auwera et al., 2013 (link)). BCFtools (Narasimhan et al., 2016 (link)), VCFtools (Danecek et al., 2011 (link)) and GATK (v4.1.8.1) were applied to left-align, normalize, extract and retain rare events allele frequency <0.1% in gnomAD v2.1.1 non-neuro subset exomes (Karczewski et al., 2020 (link)) in the VCF files. We removed variants within mean mapping quality of mapped reads (MQ) <35, quality by depth (QD) ≤2, Fisher Strand (FS) ≤60, Strand Odds Ratio (SOR) >3, MQ Rank Sum −12.5 and Read Pos Rank Sum ≤−8. Genotype quality (GQ), read-depth (RD) and allele balance (AB) were used for genotype-level quality controls. Variants within 0.25 < AB < 0.75, DP > 10, and GQ > 25 were reserved. Finally, we chose loss of function mutations and missense variants with CADD > 20. Pubvar variant annotation engine and VEP6 (release 88) were used to annotate variants2. Relatedness was calculated between each pair of samples using King v2.2.7 (Manichaikul et al., 2010 (link)). The pathogenicity of variants was interpreted according to American College of Medical Genetics (ACMG)/AMP guidelines and modified based on ClinGen recommendations. Validation of the identified variants was performed using sanger sequencing.
Zhang X., Xiao N., Cao Y., Peng Y., Lian A., Chen Y., Wang P., Gu W., Xiao B., Yu J., Wang H, & Shu L. (2023). De novo variants in MAST4 related to neurodevelopmental disorders with developmental delay and infantile spasms: Genotype-phenotype association. Frontiers in Molecular Neuroscience, 16, 1097553.
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Publication 2023
Alleles BLOOD Chromosomes Exome Family Member Genetic Diversity Genome Genome, Human Genotype INDEL Mutation Loss of Function Mutation Missense Mutation Nucleotides Parent Pathogenicity TRIO protein, human
5
Deciphering TYK2 Biomarker Associations
We obtained association estimates of the loss-of-function mutation of TYK2 gene with the following biomarkers: (i) 25 serum and urine biomarkers available in the biochemistry panel of the UK Biobank (353,579 individuals); (ii) 36 haematological traits with data derived from the summary statistics of the study by Astle et al. (173,480 European individuals)31 (link); (iii) 122 nuclear magnetic resonance-measured serum lipids and metabolites with data derived from the publicly available summary statistics provided by Kettunen et al. (24,925 individuals of European ancestry)32 ; (iv) circulating levels of 41 cytokines and growth factors with data derived from the publicly available summary statistics by Ahola-Olli et al. (8293 individuals of Finnish ancestry)33 (link); (v) 3 hemodynamic traits that were available in the UK Biobank (408,228 individuals); (vi) 5 glycaemic traits made publicly available from a series of analyses from the MAGIC Consortium (up to 133,010 individuals)34 ; and (vii) 16 blood immune cell counts derived from the summary statistics made publicly available by Orrù V et al. (3757 individuals).35 (link) The data sources for these studies are described in Supplementary Table S1.
To uncover pathophysiological mechanisms pathways from TYK2 inhibitor to autoimmune disease, we performed causal mediation analysis (CMA) for certain identified biomarkers using the mediation R package36 (link) in the UK Biobank study. We obtained an average causal mediation effect (ACME) that is transmitted via mediator to the outcome and an average direct effect that explained by the exposure as well as the proportion of explained variance by the mediator from this analysis.36 (link)
Yuan S., Wang L., Zhang H., Xu F., Zhou X., Yu L., Sun J., Chen J., Ying H., Xu X., Yu Y., Spiliopoulou A., Shen X., Wilson J., Gill D., Theodoratou E., Larsson S.C, & Li X. (2023). Mendelian randomization and clinical trial evidence supports TYK2 inhibition as a therapeutic target for autoimmune diseases. eBioMedicine, 89, 104488.
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Publication 2023
Autoimmune Diseases Biological Markers Blood Cell Count Cytokine Europeans Growth Factor Hemodynamics Lipids Loss of Function Mutation Magnetic Resonance Imaging Serum TYK2 Kinase Urine

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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
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B6.SJL-Tg(Vil-cre)997Gum/J mice are a transgenic mouse line that expresses Cre recombinase under the control of the villin promoter. This allows for Cre-mediated recombination in intestinal epithelial cells.

More about "Loss of Function Mutation"

Loss of function (LOF) mutations are genetic variations that result in the reduced or absent activity of a gene product.
These mutations can have significant impacts on biological processes and are linked to a variety of human diseases, such as genetic disorders, cancer, and neurological conditions.
Researchers studying LOF mutations rely on robust experimental protocols to ensure reproducibility and advance their understanding of these important genetic changes.
Some key aspects of LOF mutation research include: - Culturing cells: Researchers may use cell lines like BJ-hTERT cells or primary cells from animal models like C57BL/6J-Apcmin/J mice to study the effects of LOF mutations.
They often culture cells in media like DMEM supplemented with factors like Penicillin and Streptomycin. - Flow cytometry: Techniques like MoFlo cytometry can be used to analyze and sort cells with LOF mutations. - Molecular analysis: Researchers may use tools like the UVX31 meter and EnSpire Multimode Plate Reader to quantify gene expression, protein levels, and other molecular changes associated with LOF mutations. - Animal models: Mouse models like B6.SJL-Tg(Vil-cre)997Gum/J can be used to study the in vivo effects of LOF mutations.
PubCompare.ai helps scientists optimize their LOF mutation research by identifying the most reliable and effective protocols from the published literature, preprints, and patent data.
Their AI-driven comparisons provide an easy way to locate the best approaches for your studies and accelerate your scientific discovery.