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Genetic Background

Genetic Background refers to the cumulative genetic makeup of an individual or organism, including inherited traits, genetic variants, and the overall genetic composition that can influence phenotypic expression and biological functions.
This term encompasses the complex interplay between an individual's genetics and their susceptibility to diseases, response to treatments, and other relevant biological characteristics.
Understanding Genetic Background is crucial in the fields of genetics, genomics, and personalized medicine, as it enables researchers to investigate the genetic underpinnings of various phenotypes and develop targeted interventions.
Th is MeSH term provides a concise, informative overview of this important concept in the study of genetics and its applications.

Most cited protocols related to «Genetic Background»

1
Comprehensive Cancer Genomic Analysis
All samples were obtained under institutional IRB approval and with documented informed consent. A complete list of samples is given in Table S2. Whole-exome capture libraries were constructed and sequenced on Illumina HiSeq flowcells to average coverage of 118x. Whole-genome sequencing was done with the Illumina GA-II or Illumina HiSeq sequencer, achieving an average of ~30X coverage depth. Reads were aligned to the reference human genome build hg19 using an implementation of the Burrows-Wheeler Aligner, and a BAM file was produced for each tumor and normal sample using the Picard pipeline6 (link). The Firehose pipeline was used to manage input and output files and submit analyses for execution. The MuTect30 and Indelocator (Sivachenko, A. et al., manuscript in preparation) algorithms were used to identify somatic single-nucleotide variants (SSNVs) and short somatic insertions and deletions, respectively. Mutation spectra were analyzed using non-negative matrix factorization (NMF). Significantly mutated genes were identified using MutSigCV, which estimates the background mutation rate (BMR) for each gene-patient-category combination based on the observed silent mutations in the gene and noncoding mutations in the surrounding regions. Because in most cases these data are too sparse to obtain accurate estimates, we increased accuracy by pooling data from other genes with similar properties (e.g. replication time, expression level). Significance levels (p-values) were determined by testing whether the observed mutations in a gene significantly exceed the expected counts based on the background model. False Discovery Rates (q-values) were then calculated, and genes with q≤0.1 were reported as significantly mutated. Full methods details are listed in Supplementary Information.
Lawrence M.S., Stojanov P., Polak P., Kryukov G.V., Cibulskis K., Sivachenko A., Carter S.L., Stewart C., Mermel C.H., Roberts S.A., Kiezun A., Hammerman P.S., McKenna A., Drier Y., Zou L., Ramos A.H., Pugh T.J., Stransky N., Helman E., Kim J., Sougnez C., Ambrogio L., Nickerson E., Shefler E., Cortés M.L., Auclair D., Saksena G., Voet D., Noble M., DiCara D., Lin P., Lichtenstein L., Heiman D.I., Fennell T., Imielinski M., Hernandez B., Hodis E., Baca S., Dulak A.M., Lohr J., Landau D.A., Wu C.J., Melendez-Zajgla J., Hidalgo-Miranda A., Koren A., McCarroll S.A., Mora J., Crompton B., Onofrio R., Parkin M., Winckler W., Ardlie K., Gabriel S.B., Roberts C.W., Biegel J.A., Stegmaier K., Bass A.J., Garraway L.A., Meyerson M., Golub T.R., Gordenin D.A., Sunyaev S., Lander E.S, & Getz G. (2013). Mutational heterogeneity in cancer and the search for new cancer genes. Nature, 499(7457), 214-218.
Publication 2013
Diploid Cell DNA Replication Exome Gene Deletion Genes Genes, vif Genetic Background Genome, Human Insertion Mutation Multiple Acyl Coenzyme A Dehydrogenase Deficiency Mutation Neoplasms Nucleotides Patients Silent Mutation
2
Systematic Characterization of Mouse Brain
All experimental procedures were approved by the Institutional Animal Care and Use Committee (IACUC) of Allen Institute for Brain Science in accordance with NIH guidelines. All characterization was done using adult mice around ages P56 or older. The mice that were characterized were in a mixed genetic background, containing 50–75% C57BL/6 background and the remainders of 129 or other backgrounds from the various Cre lines. For systematic characterization of fluorescent proteins either by their native fluorescence or IHC, perfused brains were cryosectioned using a tape transfer technique, sections were then DAPI stained directly or following antibody staining, and images were captured using automated fluorescent microscopy. Microtome sections of 100-μm thickness from perfused brains were used for confocal imaging of fluorescently labeled cells. For systematic characterization of gene expression by colorimetric ISH or DFISH, the Allen Institute established pipelines for tissue processing, probe hybridization, image capture and data processing were utilized. Informatics signal identification, mapping, and quantification used the Allen Mouse Brain Atlas spatial mapping platform24 (link), 29 . In this pipeline, image series are preprocessed (white-balanced and cropped), then registered to a three-dimensional informatics reference atlas of the C57BL/6J mouse brain28 . This registration enables data to be displayed in 2D sections or reconstructed 3D volumes.
Madisen L., Zwingman T.A., Sunkin S.M., Oh S.W., Zariwala H.A., Gu H., Ng L.L., Palmiter R.D., Hawrylycz M.J., Jones A.R., Lein E.S, & Zeng H. (2009). A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nature neuroscience, 13(1), 133-140.
Publication 2009
Acid Hybridizations, Nucleic Adult Brain Cells Colorimetry DAPI Fluorescence Gene Expression Genetic Background Immunoglobulins Institutional Animal Care and Use Committees Mice, Inbred C57BL Mice, Laboratory Microscopy Microtomy Proteins Tissues
3
Intersectional Genetic Labeling Protocol

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Publication 2011
Alleles Biological Assay Brain Genetic Background Internal Ribosome Entry Sites Intersectional Framework Mice, Laboratory Microscopy Microscopy, Confocal Recombination, Genetic
4
Generation of Genetically Modified Mice

Er81EWS-Pea3 mice were generated following a strategy similar to that described for the generation of Er81NLZ mice [14 (link)]. In brief, a targeting vector with a cDNA coding for EWS-Pea3 was inserted in frame with the endogenous start ATG into exon 2 of the Er81 genomic locus and used for homologous recombination in W95 ES cells. EWS-Pea3 represents a fusion gene between the amino terminal of EWS and the ETS domain of Pea3 [20 (link)]. The primer pair used to specifically detect the Er81EWS-Pea3 allele was 5′-
CAGCCACTGCACCTACAAGAC-3′ and 5′-
CTTCCTGCTTGATGTCTCCTTC-3′. For the generation of TaumGFP and TauEWS-Pea3 mice, lox-STOP-lox-mGFP-IRES-NLS-LacZ-pA and lox-STOP-lox-EWS-Pea3-IRES-NLS-LacZ-pA targeting cassettes were integrated into exon 2 of the Tau genomic locus (the endogenous start ATG was removed in the targeting vectors; details available upon request). mGFP was provided by P. Caroni [25 (link)]. ES cell recombinants were screened by Southern blot analysis using the probe in the 5′ region as described previously [41 (link)]. Frequency of recombination in 129/Ola ES cells was approximately 1/3 for both Tau constructs. For the generation of PVCre mice, mouse genomic clones were obtained by screening a 129SV/J genomic library (Incyte, Wilmington, Delaware, United States). For details on the genomic structure of the mouse PV locus see [42 (link)]. An IRES-Cre-pA targeting cassette [33 (link)] was integrated into the 3′ UTR of exon 5, and ES cell recombinants were screened with a 5′ probe (oligos, 5′-
GAGATGACCCAGCCAGGATGCCTC-3′ and 5′-
CTGACCACTCTCGCTCCGGTGTCC-3′; genomic DNA, HindIII digest). The frequency of recombination in 129/Ola ES cells was approximately 1/20. Recombinant clones were aggregated with morula stage embryos to generate chimeric founder mice that transmitted the mutant alleles. In all experiments performed in this study, animals were of mixed genetic background (129/Ola and C57Bl6). Thy1spGFP transgenic mice were generated in analogy to De Paola et al. [25 (link)], and for these experiments a strain of mice with early embryonic expression was selected. Isl1Cre and Hb9Cre mouse strains have been described [33 (link),43 (link)] and Bax+/− animals were from Jackson Laboratory (Bar Harbor, Maine, United States) [27 (link)]. Timed pregnancies were set up to generate embryos of different developmental stages with all genotypes described throughout the study.
Hippenmeyer S., Vrieseling E., Sigrist M., Portmann T., Laengle C., Ladle D.R, & Arber S. (2005). A Developmental Switch in the Response of DRG Neurons to ETS Transcription Factor Signaling. PLoS Biology, 3(5), e159.
Publication 2005
2',5'-oligoadenylate Alleles Animals Chimera Clone Cells Cloning Vectors DNA, Complementary Embryo Embryonic Development Embryonic Stem Cells ETS Motif Exons Gene Fusion Genetic Background Genome Genomic Library Genotype Homologous Recombination Internal Ribosome Entry Sites LacZ Genes Mice, Laboratory Mice, Transgenic Morula Oligonucleotide Primers Pregnancy Reading Frames Recombination, Genetic Southern Blotting Strains tau-1 monoclonal antibody transcription factor PEA3
5
Functional Enrichment Analysis of Gene Sets
To test for overrepresentation of biological functions, the prioritized genes (or a list of genes of interest) are tested against gene sets obtained from MsigDB (i.e., hallmark gene sets, positional gene sets, curated gene sets, motif gene sets, computational gene sets, GO gene sets, oncogenic signatures, and immunologic signatures) and WikiPathways, using hypergeometric tests. The set of background genes (i.e., the genes against which the set of prioritized genes are tested against) is 19,283 protein-coding genes. Background genes can also be selected from gene types as described in the “Gene Mapping” section. Custom sets of background genes can also be provided by the users. Multiple testing correction (i.e., Benjamini–Hochberg by default) is performed per data source of tested gene sets (e.g., canonical pathways, GO biological processes, hallmark genes). FUMA reports gene sets with adjusted P-value ≤ 0.05 and the number of genes that overlap with the gene set > 1 by default.
Watanabe K., Taskesen E., van Bochoven A, & Posthuma D. (2017). Functional mapping and annotation of genetic associations with FUMA. Nature Communications, 8, 1826.
Publication 2017
Biological Processes Gene Products, Protein Genes Genes, vif Genetic Background Oncogenes

Most recents protocols related to «Genetic Background»

1
Standardized Phenotyping of Genetically Modified Mice
All comparisons were made between animals with the same genetic background, typically littermates, and we used male and female mice. The number of samples (n) for each comparison can be found in the individual method descriptions and are given in the corresponding figure legends. Phenotyping and data analysis were performed blind to the genotype of the mice. All values are presented either as the mean ± standard deviation (SD) or standard error of the mean (SEM). For statistical analysis, GraphPad Prism software was used. To assess differences in the mean, one-way or two-way ANOVA with Bonferroni's multiple comparison test, and unpaired two-tailed t-tests were employed. Significance was determined as P < 0.05 (*), P < 0.01 (**), P < 0.001 (***) or P < 0.0001 (****). Complete results of the statistical analyses are included in the figure legends.
Bohuslavova R., Fabriciova V., Lebrón-Mora L., Malfatti J., Smolik O., Valihrach L., Benesova S., Zucha D., Berkova Z., Saudek F., Evans S.M, & Pavlinkova G. (2023). ISL1 controls pancreatic alpha cell fate and beta cell maturation. Cell & Bioscience, 13, 53.
Publication 2023
Animals Females Genetic Background Genotype Males Mice, House neuro-oncological ventral antigen 2, human prisma Visually Impaired Persons
2
Neuron-specific Xbp1 Knockout and Inducible Xbp1s Expression
All experiments were conducted with protocols approved by the Duke University and Durham VA Medical Center Institutional Animal Care and Use Committees. These studies were conducted in accordance with the United States Public Health Service’s Policy on Humane Care and Use of Laboratory Animals. Both male and female mice were used. C57BL/6 mice were obtained from The Jackson Laboratory (Bar Harbor, ME). Xbp1f/f mice and inducible XBP1s transgenic mice (TRE-XBP1s) were kindly provided by Dr. Laurie Glimcher32 (link) and Dr. Joseph Hill33 (link), respectively. We crossed TRE-XBP1s mice with Camk2a-tTA (JAX #007004) mice to generate double transgenic mice with inducible expression of Xbp1s in neurons: TRE-XBP1s;Camk2a-tTA mice (XBP1s-TG). In XBP1s-TG mice, Xbp1s expression is suppressed by doxycycline (Dox) presented in the drinking water. Upon Dox withdrawal, Xbp1s expression is activated. To generate neuron-specific Xbp1 knockout mice, Xbp1f/f mice were cross-bred with Emx1Cre/Cre mice (JAX #005628) to obtain Xbp1f/f;Emx1-Cre (Xbp1-cKO) mice. To visualize the pattern of Cre expression controlled by the Camk2a promoter, CAG-SUMO mice (generated previously in our lab)34 (link) were mated with Camk2a-Cre (JAX #005359). Note, all mouse lines were on a C57BL/6 genetic background. Primers for genotyping are listed in Supplementary Table 2.
Wang Z., Li Q., Kolls B.J., Mace B., Yu S., Li X., Liu W., Chaparro E., Shen Y., Dang L., del Águila Á., Bernstock J.D., Johnson K.R., Yao J., Wetsel W.C., Moore S.D., Turner D.A, & Yang W. (2023). Sustained overexpression of spliced X-box-binding protein-1 in neurons leads to spontaneous seizures and sudden death in mice. Communications Biology, 6, 252.
Publication 2023
Animals, Laboratory Doxycycline Females Genetic Background Institutional Animal Care and Use Committees Males Mice, Inbred C57BL Mice, Knockout Mice, Laboratory Mice, Transgenic Neurons Oligonucleotide Primers X-box binding protein 1, human
3
Nrxn1α Deletion Mouse Models
Mice were group housed in cages of 2 to 5 on a 12-hour light/12-hour dark cycle with food and water provided ad libitum. The mice used in this study for behavioral testing were between 3–5 months of age, including both males and females.
Mice with Nrxn1α promoter and exon 1 deletion (ΔExon1) were described previously [9 (link)] and have been maintained in C57BL/6J background. Mice with Nrxn1α exon 9 deletion (ΔExon9) were generated by crossing an exon 9 floxed allele of Nrxn1α (Nrxn1tm1a(KOMP)Wtsi from MRC Mary Lyon Center, Harwell, UK) [13 (link)] with mice carrying UBC-CreERT2 [70 (link)]. An unexpected leaky activity of Cre in male gametes [33 (link)] carrying both floxed exon 9 of Nrxn1α and UBC-Cre-ERT2 leads to a germline loss of exon 9 (ΔExon9). The deletion of exon 9 was confirmed by PCR analysis using primers flanking the deleted region and within the exon 9 sequence. To study a CNV identified in an individual on the autism spectrum [27 (link)], mouse homologue of the ~20 kb deleted region at intron 17 of Nrxn1α was identified and deleted using the CRISPR/Cas9-medicated genomic editing approach. Two sgRNAs (5’ AATATGTGGGCAAGCTGGGT TGG 3’ and 5’ GAAATGGTACCTTTGATCTA AGG 3’) flanking the deletion region in intron 17 of Nrxn1α were injected together with Cas9 protein into 1-cell zygote of C57BL/6J/SJL genetic background. The target deletion was confirmed by PCR and sequencing analyses using primers flanking the deleted region and deletion carriers (ΔIntron17) were back crossed to C57BL/6J for 5 more generations to collect littermates for behavioral phenotyping.
To generate experimental animals used in this study, heterozygous males were bred with heterozygous females to generate mice with homozygous (ΔExon9/ΔExon9; ΔIntron17/ΔIntron17) or heterozygous (ΔExon9/+; ΔIntron17/+) deletions, as well as WT littermates (+/+). We noted that mice carrying homozygous deletion of exon 9 (ΔExon9/ΔExon9) were significantly underrepresented with WT:Het:Homo ratio as 48:90:29, in contrast to the expected ratio of 42:83:42, indicating sub-viability in mice carrying a complete loss of Nrxn1α. To generate mice carrying ΔExon1, heterozygous carriers of ΔExon1 were bred with WT mice to collect heterozygotes and WT for experiments described in this study.
Xu B., Ho Y., Fasolino M., Medina J., O’Brien W.T., Lamonica J.M., Nugent E., Brodkin E.S., Fuccillo M.V., Bucan M, & Zhou Z. (2023). Allelic contribution of Nrxn1α to autism-relevant behavioral phenotypes in mice. PLOS Genetics, 19(2), e1010659.
Publication 2023
Alleles Animals, Laboratory Cells Clustered Regularly Interspaced Short Palindromic Repeats CRISPR-Associated Protein 9 Deletion Mutation Exons Females Food Gametes Gene Deletion Genetic Background Germ Line Heterozygote Homo Homozygote Introns Males Mice, House mitogen-activated protein kinase 3, human Oligonucleotide Primers Pervasive Development Disorders Sequence Analysis Zygote
4
Female Transgenic SOD1G93A Mouse Model
Female transgenic SOD1G93A mice on C57BL/6JOlaHsd (C57G93A) and 129S2/Sv (129SvG93A) genetic background, and their corresponding non-transgenic (NTG) female littermates, were used in this study [23 , 25 (link)]. The animals have been housed under SPF (specific pathogen-free) standard conditions (22 ± 1 °C, 55 ± 10% relative humidity, and 12-h light/dark schedule), 3–4 per cage, with free access to food (standard pellet, Altromin, MT, Rieper) and water. Procedures involving animals and their care were conducted in conformity with the institutional guidelines of the Mario Negri Institute for Pharmacological Research, Milan, Italy, IRFMN, which are in compliance with national (D.lgs 26/2014; authorisation no. 783/2016-PR issued on August 8, 2016, by Ministry of Health) and Mario Negri institutional regulations and policies providing internal authorisation for persons conducting animal experiments (quality management system certificate—UNI EN ISO 9001:2008—reg. N° 6121); the NIH Guide for the Care and Use of Laboratory Animals (2011 edition); and EU directives and guidelines (EEC Council Directive 2010/63/UE). Animal studies were approved by the Mario Negri Institute Animal Care and Use Committee and by the Italian Ministerial Decree no. 246/2020-PR.
Margotta C., Fabbrizio P., Ceccanti M., Cambieri C., Ruffolo G., D’Agostino J., Trolese M.C., Cifelli P., Alfano V., Laurini C., Scaricamazza S., Ferri A., Sorarù G., Palma E., Inghilleri M., Bendotti C, & Nardo G. (2023). Immune-mediated myogenesis and acetylcholine receptor clustering promote a slow disease progression in ALS mouse models. Inflammation and Regeneration, 43, 19.
Publication 2023
Animals Animals, Laboratory Animals, Transgenic Females Food Genetic Background Humidity Light Mice, Transgenic Ministers Specific Pathogen Free Training Programs
5
Characterization of GBS β-h/c Mutant
GBS wild type (WT) strain CNCTC 10/84 (1169‐NT1; ATCC 49447, serotype V) and the isogenic, β‐h/c‐deficient, in‐frame cylEΔcat mutant (referred to as β‐h/c KO) were used. The WT CNCTC 10/84 strain is hyperhemolytic in comparison to other GBS strains. The cylE KO strain (β‐h/c KO) is nonhemolytic, lacks production of the granadaene pigment, and is in the CNCTC 10/84 genetic background. All bacteria were grown at 37°C in trypticase soy (TS) broth and plated on TS agar.
Kuperwaser F., Avital G., Vaz M.J., Noble K.N., Dammann A.N., Randis T.M., Aronoff D.M., Ratner A.J, & Yanai I. (2023). Host inflammatory dynamics reveal placental immune modulation by Group B Streptococcus during pregnancy. Molecular Systems Biology, 19(3), e11021.
Publication 2023
Agar Bacteria Genetic Background Pigmentation Reading Frames Strains trypticase-soy broth

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C57bl 6j mice by Charles River Laboratories
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More about "Genetic Background"

Genetic Background is a crucial concept in the fields of genetics, genomics, and personalized medicine.
It refers to the cumulative genetic makeup of an individual or organism, including inherited traits, genetic variants, and the overall genetic composition that can influence phenotypic expression and biological functions.
This complex interplay between an individual's genetics and their susceptibility to diseases, response to treatments, and other relevant biological characteristics is essential for understanding various phenotypes and developing targeted interventions.
The C57BL/6J mouse strain, also known as the C57BL/6 or B6 mouse, is a widely used model in genetic research due to its well-characterized Genetic Background.
These mice are known for their resilience, longevity, and susceptibility to diet-induced obesity, making them a valuable tool for studying metabolic disorders, such as those associated with the D12492 high-fat diet.
Additionally, the use of tamoxifen in C57BL/6 mice has become a common technique for inducing gene expression or recombination, allowing researchers to investigate the impact of specific genetic factors on phenotypes.
Beyond mouse models, understanding Genetic Background is crucial in human studies as well.
Factors such as genetic variants, ancestry, and gene-environment interactions can influence an individual's susceptibility to diseases, response to treatments, and overall health.
In the context of personalized medicine, this knowledge is leveraged to develop targeted interventions and optimize therapeutic outcomes.
To enhance the reproducibility and accuracy of Genetic Background research, platforms like PubCompare.ai can be utilized.
This AI-driven platform helps researchers easily locate the most relevant protocols from literature, pre-prints, and patents, while providing AI-driven comparisons to identify the best protocols and products.
By streamlining the research process and leveraging the power of AI, researchers can boost their findings and gain deeper insights into the complex interplay between Genetic Background and various biological phenomena.
Whether working with mouse models or human subjects, understanding Genetic Background is essential for advancing our knowledge in the fields of genetics, genomics, and personalized medicine.
By incorporating these insights and utilizing innovative tools like PubCompare.ai, researchers can drive forward groundbreaking discoveries and improve the overall understanding of the genetic underpinnings of health and disease.