Identifying genes for neurobehavioural traits in rodents: progress and pitfalls

Baud, Amelie; Flint, Jonathan

doi:10.1242/dmm.027789

Cited by 20 publications

(22 citation statements)

References 132 publications

(177 reference statements)

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“…Complementary strategies are thus required to narrow down the list of candidate genes, such as the generation of congenic lines or/and the use of integrative genomic approaches [as discussed in 17]. Alternative approaches rely on the use of panels of lines that show a higher level of recombinant events, as a result of crossing parental strains for multiple generations, such as recombinant inbred strains or heterogeneous stocks [as discussed in 18, for a striking harvest of results derived from the study of a heterogeneous stock, see 19]. The first complex-trait gene identified is the Cd36 gene, which causes insulin resistance, hyperlipidemia and hypertension in the spontaneously hypertensive rat (SHR) [20, 21].…”

Section: Results and Conclusionmentioning

confidence: 99%

Rat models of human diseases and related phenotypes: a systematic inventory of the causative genes

Szpirer¹

2020

Preprint

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The rat has been used for a long time as the model of choice in several biomedical disciplines. Numerous inbred strains have been isolated, displaying a wide range of phenotypes and providing many models of human traits and diseases. Rat genome mapping and genomics was considerably developed in the last decades. The availability of these resources has stimulated numerous studies aimed at discovering disease genes by positional identification. Numerous rat genes have now been identified that underlie monogenic or complex diseases and remarkably, these results have been translated to the human in a significant proportion of cases, leading to the identification of novel human disease susceptibility genes, helping in studying the mechanisms underlying the pathological abnormalities and also suggesting new therapeutic approaches. In addition, reverse genetic tools have been developed. Several genome-editing methods were introduced to generate targeted mutations in genes the function of which could be clarified in this manner [generally these are knockout (KO) mutations]. Furthermore, even when the human gene causing a disease is identified, mutated rat strains (in particular KO strains) were created to analyze the gene function and the disease pathogenesis. Today, about 300 rat genes have been identified as underlying diseases or playing a key role in critical biological processes that are altered in diseases. This article provides the reader with an inventory of these genes.

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Section: Results and Conclusionmentioning

confidence: 99%

Rat models of human diseases and related phenotypes: a systematic inventory of the causative genes

Szpirer¹

2020

Preprint

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“…There were several genes that have been reported to be of functional signi cance in other species. SLIT2, PACRGL, GPR125, DHX15, SOD3 and KCNIP4 were identi ed in a mice QTL interval linked to thermal nociception [24,25]. TBC1D14 has a critical development role for RAB-GAP-mediated protein transport in early embryogenesis in mouse, while its paralog, TBC1D12, has been implicated as a candidate gene for environmental genetic adaptation [26].…”

Section: Resultsmentioning

confidence: 99%

Genomic signatures of divergent selection for production and adaptation in domestic goats (Capra hircus)

Mwacharo¹,

Kim²,

Elbeltagy³

et al. 2019

Preprint

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Background : Goats are distributed worldwide and include many breeds with marked phenotypic variation. Both natural and human driven processes have shaped their genomes. Here, 52K genome-wide SNP genotypes were used to investigate signatures of divergent selection between indigenous goats from an arid hot environment in Egypt and breeds developed under temperate environments in Europe. Three selection signature approaches were used, the di derivative of F ST , iHS and Rsb. Results: Out of a total of 36 candidate regions that were detected to be under selection by the three approaches, the analysis detected nine regions with the strongest selection signatures spanning 134 genes of which 68 were the most significantly functionally enriched. In addition to well-known genes affecting dairy traits ( LAP3 , ABCG2 , MEPE , IBSP , MED28 ) and body weight and stature ( LCORL , NCAPG , CCSER1 , DCAF16 ) in several mammalian species, we found evidence for selection in regions spanning genes implicated in the regulation of fatty acid synthesis and metabolic pathways ( PI4K2B and PPARGC1A ), inflammatory gene expression and autoimmune response pathways ( CXCL8 , HERC5 , RGS18 , TROVE2 ) and spermatogenesis ( SPATA18 , LAP3 ). Other genes not reported before in goats included SLIT2 , PACRGL , GRP125 , DHX15 , SOD3 and KCNIP4 which have been associated with thermal nociception in mice. We also detected a paralog of TBC1D12 , namely TBC1D14 , in one of the candidate regions. TBC1D12 has been linked to environmental adaptation in sheep. Gene ontology analysis revealed the 68 candidate genes were highly enriched in two biological processes viz regulation of G protein-coupled receptor signaling pathway (GO:0045744) and cellular response to stress (GO:0033554). Conclusions: Our results provide evidence that goat genomes have evolved, in part, via diverse positive selection directed at breed formation, at past and recent genetic improvement and adaptation to environments. Based on their uniqueness, these breed-group specific signatures of selection can be considered to be footprints of divergence which may be useful in characterizing genome architecture and diversity in domestic animals and for targeted genetic improvement.

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“…Genetic background effects can in fact give great biological insight as this common source of variation can be used to help identify modifier loci (87). For example, a modifier locus for human Dravet's syndrome (a severe, infant-onset epileptic encephalopathy) was identified using the straindependent epilepsy phenotype of a mouse carrying a Scn1a (sodium voltage-gated channel subunit 1) mutation (88).…”

Section: The Importance Of Variabilitymentioning

confidence: 99%

Mouse models of neurodegeneration: Know your question, know your mouse

Fisher

Bannerman

2019

Sci. Transl. Med.

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Overline: Neurodegenerative Disease Single Sentence Summary:We can now create an unprecedented set of mouse models for understanding neurodegeneration and we need to carefully consider which model best fits our research question and how to learn from the variability within and between studies. AbstractMany mutant mouse strains have been developed to investigate neurodegenerative diseases, but variability among mouse studies has led to questioning of the value of these mouse models. Here, we appraise various mouse models for dissecting neurodegenerative mechanisms and emphasise the importance of asking appropriate scientific questions and understanding variability among and within studies. In therapeutics research, we suggest that not embracing this variability in mouse models may contribute to translational failure in human patients.

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Identifying genes for neurobehavioural traits in rodents: progress and pitfalls

Cited by 20 publications

References 132 publications

Rat models of human diseases and related phenotypes: a systematic inventory of the causative genes

Rat models of human diseases and related phenotypes: a systematic inventory of the causative genes

Genomic signatures of divergent selection for production and adaptation in domestic goats (Capra hircus)

Mouse models of neurodegeneration: Know your question, know your mouse

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