Advantages, disadvantages and research progress on strategies for screening and identifying functional genes

doi:10.16352/j.issn.1001-6325.2022.06.010

Abstract

Abstract: The screening and identification of functional genes is a key step to deeply understand various biological phenotypes. Forward genetics including traditional genetics, genome-wide association analysis, the comparison of gene expression profiles and bioinformatics, and reverse genetics including cDNA library, RNA interference, CRISPR-Cas9 technology, insertion mutation as well as model organisms have been applied to screening functional genes. Different methods have their own advantages and disadvantages and technology combination to screen and to identify functional genes is a good choice of strategy.

Key words: functional genes, forward genetics, reverse genetics, bioinformatics, model organism

CLC Number:

LIU Xu, CHANG De, WANG Jun-feng. Advantages, disadvantages and research progress on strategies for screening and identifying functional genes[J]. Basic & Clinical Medicine, 2022, 42(6): 969-974.

0
/ / Recommend

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

URL: http://journal11.magtechjournal.com/Jwk_jcyxylc/EN/10.16352/j.issn.1001-6325.2022.06.010

http://journal11.magtechjournal.com/Jwk_jcyxylc/EN/Y2022/V42/I6/969

References

[1] Nagy LG, Merényi Z, Hegedüs B, et al. Novel phylogenetic methods are needed for understanding gene function in the era of mega-scale genome sequencing[J]. Nucleic Acids Res, 2020, 48: 2209-2219.
[2] 方福德.有关“组”(-ome)和“组学”(-omics)的几个名词[J].基础医学与临床,2011,31(4):封2.
[3] Funato H, Miyoshi C, Fujiyama T, et al. Forward-genetics analysis of sleep in randomly mutagenized mice[J]. Nature, 2016, 539: 378-383.
[4] Nogales A, Martínez-Sobrido L. Reverse genetics approaches for the development of influenza vaccines[J]. Int J Mol Sci, 2017, 18: 20. doi: 10.3390/ijms18010020.
[5] Gao B, Guo J, She C, et al. Mutations in IHH, encoding Indian hedgehog, cause brachydactyly type A-1[J]. Nat Genet, 2001, 28: 386-388.
[6] Buniello A, MacArthur JAL, Cerezo M, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019[J]. Nucleic Acids Res, 2019, 47: D1005-D1012.
[7] Luo C, Wang F, Ren X, et al. Identification of a molecular signaling gene-gene regulatory network between GWAS susceptibility genes ADTRP and MIA3/TANGO1 for coronary artery disease[J]. Biochim Biophys Acta Mol Basis Dis, 2017, 1863: 1640-1653.
[8] Speakman JR, Loos RJF, O'Rahilly S, et al. GWAS for BMI: a treasure trove of fundamental insights into the genetic basis of obesity[J]. Int J Obes (Lond), 2018, 42: 1524-1531.
[9] Bovijn J, Jackson L, Censin J, et al. GWAS identifies risk locus for erectile dysfunction and implicates hypothalamic neurobiology and diabetes in etiology[J]. Am J Hum Genet, 2019, 104: 157-163.
[10] Slotta-Huspenina J, Drecoll E, Feith M, et al. MicroRNA expression profiling for the prediction of resistance to neoadjuvant radiochemotherapy in squamous cell carcinoma of the esophagus[J]. J Transl Med, 2018, 16: 1-9.
[11] Ruggles KV, Krug K, Wang X, et al. Methods, tools and current perspectives in proteogenomics[J]. Mol Cell Proteomics, 2017, 16: 959-981.
[12] Liu X, Wu J, Zhang D, et al. Identification of potential key genes associated with the pathogenesis and prognosis of gastric cancer based on integrated bioinformatics analysis[J]. Front Genet, 2018, 9: 265. doi: 10.3389/fgene.2018.00265.
[13] Wong FS, Karttunen J, Dumont C, et al. Identification of an MHC class I-restricted autoantigen in type 1 diabetes by screening an organ-specific cDNA library[J]. Nat Med, 1999;5:1026-1031.
[14] Mamta B, Rajam MV. RNAi technology: a new platform for crop pest control[J]. Physiol Mol Biol Plants, 2017, 23: 487-501.
[15] Mohr SE, Smith JA, Shamu CE, et al. RNAi screening comes of age: improved techniques and complementary approaches[J]. Nat Rev Mol Cell Biol, 2014, 15: 591-600.
[16] Shalem O, Sanjana NE, Zhang F. High-throughput functional genomics using CRISPR-Cas9[J]. Nat Rev Genet, 2015, 16: 299-311.
[17] Wade M. High-throughput silencing using the CRISPR-Cas9 system: a review of the benefits and challenges[J]. J Biomol Screen, 2015, 20: 1027-1039.
[18] Weber J, de la Rosa J, Grove CS, et al. PiggyBac transposon tools for recessive screening identify B-cell lymphoma drivers in mice[J]. Nat Commun, 2019, 10: 1-16.
[19] Nielsen J. Yeast systems biology: model organism and cell factory[J]. Biotechnol J, 2019,14:e1800421. doi: 10.1002/biot.201800421.
[20] Beckmann PJ, Largaespada DA. Transposon insertion mutagenesis in mice for modeling human cancers: critical insights gained and new opportunities[J]. Int J Mol Sci, 2020,21:1172. doi: 10.3390/ijms21031172.
[21] Ranzani M, Annunziato S, Adams DJ, et al. Cancer gene discovery: exploiting insertional mutagenesis[J]. Mol Cancer Res, 2013, 11: 1141-1158.
[22] Zwaal RR, Broeks A, van Meurs J, et al. Target-selected gene inactivation in Caenorhabditis elegans by using a frozen transposon insertion mutant bank[J]. Proc Natl Acad Sci U S A, 1993, 90: 7431-7435.
[23] Thibault ST, Singer MA, Miyazaki WY, et al. A complementary transposon tool kit for Drosophila melanogaster using P and piggyBac[J]. Nat Genet, 2004, 36: 283-287.
[24] Rad R, Rad L, Wang W, et al. PiggyBac transposon mutagenesis: a tool for cancer gene discovery in mice[J]. Science, 2010, 330: 1104-1107.
[25] Weber J, de la Rosa J, Grove CS, et al. PiggyBac transposon tools for recessive screening identify B-cell lymphoma drivers in mice[J]. Nat commun, 2019, 10: 1-16.
[26] 由磊. 全基因组筛选胰腺癌耐药相关基因[D].北京协和医学院,2010.
[27] 常德. 全基因组筛选和鉴定ARPC1B基因在胰腺癌转移中的作用和机理[D].北京协和医学院,2011.