- Research article
- Open Access
Exome sequencing of senescence-accelerated mice (SAM) reveals deleterious mutations in degenerative disease-causing genes
- Kumpei Tanisawa1, 2,
- Eri Mikami1, 2, 3,
- Noriyuki Fuku1,
- Yoko Honda1,
- Shuji Honda1,
- Ikuro Ohsawa4,
- Masafumi Ito5,
- Shogo Endo6,
- Kunio Ihara7,
- Kinji Ohno8,
- Yuki Kishimoto9,
- Akihito Ishigami9,
- Naoki Maruyama9,
- Motoji Sawabe10,
- Hiroyoshi Iseki11,
- Yasushi Okazaki11,
- Sanae Hasegawa-Ishii12,
- Shiro Takei12,
- Atsuyoshi Shimada12,
- Masanori Hosokawa12,
- Masayuki Mori13,
- Keiichi Higuchi13,
- Toshio Takeda14,
- Mitsuru Higuchi15 and
- Masashi Tanaka1Email author
© Tanisawa et al.; licensee BioMed Central Ltd. 2013
Received: 26 November 2012
Accepted: 19 March 2013
Published: 15 April 2013
Senescence-accelerated mice (SAM) are a series of mouse strains originally derived from unexpected crosses between AKR/J and unknown mice, from which phenotypically distinct senescence-prone (SAMP) and -resistant (SAMR) inbred strains were subsequently established. Although SAMP strains have been widely used for aging research focusing on their short life spans and various age-related phenotypes, such as immune dysfunction, osteoporosis, and brain atrophy, the responsible gene mutations have not yet been fully elucidated.
To identify mutations specific to SAMP strains, we performed whole exome sequencing of 6 SAMP and 3 SAMR strains. This analysis revealed 32,019 to 38,925 single-nucleotide variants in the coding region of each SAM strain. We detected Ogg1 p.R304W and Mbd4 p.D129N deleterious mutations in all 6 of the SAMP strains but not in the SAMR or AKR/J strains. Moreover, we extracted 31 SAMP-specific novel deleterious mutations. In all SAMP strains except SAMP8, we detected a p.R473W missense mutation in the Ldb3 gene, which has been associated with myofibrillar myopathy. In 3 SAMP strains (SAMP3, SAMP10, and SAMP11), we identified a p.R167C missense mutation in the Prx gene, in which mutations causing hereditary motor and sensory neuropathy (Dejerine-Sottas syndrome) have been identified. In SAMP6 we detected a p.S540fs frame-shift mutation in the Il4ra gene, a mutation potentially causative of ulcerative colitis and osteoporosis.
Our data indicate that different combinations of mutations in disease-causing genes may be responsible for the various phenotypes of SAMP strains.
Aging is one of the most complex biological processes that are regulated by both genetic and environmental factors, but its molecular basis remains largely unknown . Senescence-accelerated mice (SAM) are a series of inbred strains developed from the AKR/J strain, consisting of 9 senescence-prone strains (SAMP) and 4 senescence-resistant strains (SAMR) [2, 3]. Compared with SAMR strains, which show normal senescence, SAMP strains exhibit accelerated-senescence phenotypes such as a short life span and early onset of various age-related pathological changes . These SAM strains have therefore been used as a model to elucidate the mechanism of aging.
It has remained unknown why SAM strains exhibit different phenotypes, even though they were derived from a common ancestor [2, 3]. Genetic analyses by use of biochemical and immunological markers and endogenous murine leukemia virus (MuLV) proviral markers revealed that each SAM strain constitutes a genetically distinct group. Comparisons of the SAM strains with their parental AKR/J strain indicated significant differences in genetic background between them, corroborating the hypothesis of the involvement of other strains, which underscores the probability of accidental outbreeding of the AKR/J strain in the course of the development of SAM [5, 6].
Despite intense characterization of SAM strains, the genes responsible for accelerated senescence and pathologic changes in SAMP strains remain unidentified except for mutations in the Apoa2, Sfrp4, and Fgf1 genes [7–9]. Xia et al. performed genotyping for 581 microsatellite markers in 13 established SAM strains, and identified 4 loci that were different between the SAMP and SAMR strains , although the responsible genes remain unknown. Furthermore, genetic analysis of crosses between the SAMP1 and SAMR1 strains also suggested that combinations of multiple gene mutations are responsible for the phenotypes .
Recent advances in next-generation sequencing technologies have made it possible to rapidly determine the DNA sequence of the whole genome of individual humans [12, 13]. As an alternative approach to whole-genome sequencing, whole-exome sequencing is an efficient strategy with regard to reducing the cost and workload [14, 15]. Exome sequencing enables us to obtain information on functionally important coding regions. Although this type of sequencing is useful for identification of the cause of Mendelian disorders [16, 17], it is difficult to explore genes responsible for complex traits by using this approach. The difficulty in identification of combined effects of various variants in humans is mainly ascribable to the presence of heterozygosity as well as homozygosity in humans . In contrast, inbred mouse strains such as SAM strains are useful models to analyze the combined effects of genes because we can focus on homozygous variations only.
In the present study, we performed whole exome sequencing of 6 SAMP and 3 SAMR strains to identify the single-nucleotide variations (SNVs) in their entire exomes. We hypothesized that the accelerated-senescence phenotypes and short life span observed in SAMP strains are caused by coding-region mutations that are present specifically in SAMP strains but are absent in the SAMR strains. We obtained a full view of the exome signature of SAM strains and report herein several mutations that potentially cause various pathogenic phenotypes. Our data demonstrate that this innovative approach, whole-exome sequencing, is paving the way to the unraveling of the genetic mechanisms of accelerated senescence and pathogenic phenotypes in mouse models.
Whole-exome sequencing revealed exonic profiles of SAM strains
Number of mapped reads and read depth obtained through exome sequencing of 11 mouse strains
Target exons with no coverage
Total Target bases
Target bases not covered
Percent of target bases not covered
Reads in target regions
Reads off target regions
Percent of reads in target regions
Coverage at 1×
Coverage at 5×
Coverage at 10×
Coverage at 20×
Average depth of coverage within target regions
Number of SNVs identified through exome sequencing of 11 mouse strains
Total Gain of Stops
No novel exonic mutations commonly detected among SAMP strains
Missense SNVs detected among all of the SAMP strains, but absent in the SAMR and AKR/J strains
Amino acid change
SNV carriers in 17 inbred strains of laboratory mice
8-oxoguanine DNA-glycosylase 1
tRNA splicing endonuclease 2 homolog (S. cerevisiae)
129P2/OlaHsd, 129S1/SvImJ, 129S5SvEvBrd, DBA/2J, LP/J, NOD/ShiLtJ, NZO/HlLtJ, WSB/EiJ
methyl-CpG binding domain protein 4
129P2/OlaHsd, 129S1/SvImJ, 129S5SvEvBrd, DBA/2J, LP/J, NOD/ShiLtJ, NZO/HlLtJ
DNA segment, Chr 6, Wayne State University 116, expressed(WASH complex subunit FAM21)
129P2/OlaHsd, 129S1/SvImJ, 129S5SvEvBrd, DBA/2J, LP/J, NOD/ShiLtJ, NZO/HlLtJ
129P2/OlaHsd, 129S1/SvImJ, 129S5SvEvBrd, DBA/2J, LP/J, NOD/ShiLtJ, NZO/HlLtJ
monooxygenase, DBH-like 1
monooxygenase, DBH-like 1
Top 5 overrepresented GO terms within the 6 genes including missense SNVs detected among all of the SAMP strains, but absent in the SAMR and AKR/J strains
Number of reference genes in the category
Number of genes in the gene set and also in the category
Expected number in genes in the gene set
response to stress
Alox5, Mbd4, Ogg1
cellular response to DNA damage stimulus
response to DNA damage stimulus
The Ogg1 p.R304W mutation was previously observed in all of the SAMP strains, but this same mutation was also detected in NZB/N, NFS/N, SJL/J, and NOD/ShiLtJ strains . The Ogg1 gene encodes the enzyme 8-oxoguanine DNA glycosylase, by which oxidatively modified bases are repaired [24, 25]. The methyl-CpG-binding domain protein, encoded by the Mbd4 gene, is also a DNA repair enzyme that is responsible for removing mismatched thymine or uracil within methylated CpG sites . Similar to Ogg1 p.R304W, Mbd4 p.D129N was previously found in normal mice strains including 129P2/OlaHsd, 129S1/SvImJ, 129S5SvEvBrd, DBA/2J, LP/J, NOD/ShiLtJ, and NZO/HlLtJ . It is interesting that all of the SAMP strains as well as the NOD/ShiLtJ strain share these genes that are involved in DNA repair, i.e., Ogg1 and Mbd4. NOD/ShiLtJ is a mouse model of type 1 diabetes, showing a short life span [27, 28]. Nevertheless, we should be careful to conclude that the combination of these mutations regulates the accelerated-senescence phenotype of SAMP, because the short life span of NOD/ShiLtJ is generally attributed to diabetes caused by insulitis.
Unique deleterious mutations identified in each substrain
Novel deleterious mutations detected among multiple SAMP strains, but absent in the SAMR and AKR/J strains
Nucleotide change (cDNA)
Amino acid change
LIM domain binding 3
SAMP1/SkuSlc,SAMP3/SlcIdr,SAMP6/TaSlc, SAMP10/TaSlc, SAMP11/SlcIdr
gap junction protein, alpha 3
SAMP3/SlcIdr,SAMP6/TaSlc, SAMP10/TaSlc, SAMP11/SlcIdr
SAMP3/SlcIdr, SAMP10/TaSlc, SAMP11/SlcIdr
TBC1 domain family, member 9B
zinc finger, MYND-type containing 15
protocadherin beta 2
protocadherin beta 6
Novel deleterious mutations specific to SAMP6/TaSlc
Nucleotide change (cDNA)
Amino acid change
zinc finger, DHHC domain containing 12
laminin gamma 3
interleukin 4 receptor, alpha
ATP-binding cassette, sub-family A (ABC1), member 7
DIP2 disco-interacting protein 2 homolog B
coronin, actin-binding protein 1B
Novel deleterious mutations specific to SAMP8/TaSlc
Nucleotide change (cDNA)
Amino acid change
lymphocyte antigen 75
ligand of numb-protein X 1
myosin, heavy polypeptide 11, smooth muscle
apoptosis-inducing factor, mitochondrion-associated 3
We also detected 52 novel deleterious mutations in SAMR strains (Additional file 1: Table S11). These results are not surprising, because it has been reported that SAMR strains exhibit several diseases such as non-thymic lymphoma, histiocytic sarcoma, and ovarian cysts , although the SAMR strains have been used as control groups against the SAMP strains. Novel deleterious mutations including Fbxl13 p.S734N, Sh3bp5l p.R217W, Tnrc6a p.A278V, and Zkscan2 p.C232X were detected among all of the SAMP strains in addition to being found in several SAMR strains (Additional file 1: Table S12). These mutations may be associated with susceptibility to diseases in SAMP strains as well as in SAMR ones.
Prxp.R167C mutation in SAMP3, SAMP10, and SAMP11 strains
Ldb3p.R473W mutation in all of SAMP strains except for SAMP8
In the Ldb3 gene, encoding LIM domain-binding protein 3, the p.R467W mutation (SIFT score: 0.02, PolyPhen-2 score: 0.968) was detected in all of the SAMP strains except for SAMP8/TaSlc (Table 5). Ldb3 is a component of the sarcomere Z disk protein complex expressed in cardiac and skeletal muscles, and it is connected to calsarcin-1 and α-actinin . Mutations in the Ldb3 gene are responsible for myofibrillar myopathy and dilated cardiomyopathy in humans [37, 38]. In addition, LDB3 exon 4 is aberrantly spliced in myotonic dystrophy type 1 . Pathological changes in skeletal and cardiac muscles of SAMP strains, however, have not been fully analyzed.
Gja3p.S405P mutation in SAMP3, SAMP6, SAMP10, and SAMP11 strains
We detected the Gja3 p.S405P mutation (SIFT score: 0.09, PolyPhen-2 score: 0.917) in 4 SAMP strains (SAMP3/SlcIdr, SAMP6/TaSlc, SAMP10/TaSlc and SAMP11/SlcIdr; Table 5). Gap junction protein alpha 3, encoded by Gja3, is specifically expressed in the plasma membrane of lens fiber cells to form gap junctions . Gap junctions directly connect the cytoplasm of adjacent cells, and allow various molecules and ions to pass freely between cells, functioning for the maintenance of osmotic and metabolic balance in the avascular lens. A large number of studies have reported the association of mutations of the GJA3 gene with cataract in humans [41, 42].
Il4ra p.S540fs and Zdhhc12p.R112C mutations in the SAMP6 strain
The Zdhhc12 p.R112C mutation (SIFT score: 0.000, PolyPhen-2 score: 0.999) was also detected uniquely in SAMP6 (Table 6). Zinc-finger DHHC domain-containing protein 12, encoded by the Zdhhc12 gene, has a predicted DHHC cysteine-rich palmitoyl acyltransferase domain . Several gene mutations in the Zdhhc family have been implicated in human diseases and abnormal phenotypes of mice. Remarkably, Zdhhc13-truncated mutant mice develop alopecia, osteoporosis, and systemic amyloidosis ; and the osteoporotic phenotype can be explained by the finding that protein palmitoylation regulates osteoblast differentiation through bone morphogenesis protein (BMP)-induced Osterix expression . Thus we speculate that Zdhhc12 p.R112C mutation might contribute to the osteoporotic phenotype in SAMP6.
Aifm3p.K582N mutation specific to SAMP8
Five detected deleterious mutations were unique to the SAMP8/TaSlc strain, which show deficits in learning and memory, emotional disorder, and abnormal circadian rhythm at early ages (Table 7) [52, 53]. It is remarkable that the K582N mutation in the Aifm3 gene (SIFT score: 0.01, PolyPhen-2 score: 0.879), encoding apoptosis-inducing factor mitochondrion-associated protein 3, was detected in SAMP8/TaSlc. Although the function of Aifm3 has not been fully elucidated, it has been reported that Aifm3 shares 35% homology with Aifm1 and that overexpression of Aifm3 induces apoptosis in HEK 293 cells . Because the lysine at 582 in Aifm3 is highly conserved among mammalian species, this p.K582N mutation therefore may alter the function of Aifm3, contributing to the mitochondrial dysfunction in SAMP8 mice.
Whole-exome sequencing identified new candidate mutations responsible for age-related phenotypes in SAMP strains
We detected Ogg1 p.R304W and Mbd4 p.D129N deleterious mutations, which were common to all of the SAMP strains, but absent in the SAMR and AKR/J strains; although these 2 mutations were also detected in other mouse strains. It was already investigated as to whether a defect in Ogg1 protein would affect the life spans in SAMP strains. Mori et al. reported that hybrid mice with the homozygous mutation in Ogg1 p.R304W exhibited a complete loss of the glycosylase activity as well as a higher level of 8-oxoguanine in their hepatic nuclear DNA . However, the average life span of the SAMP1×B10.BR hybrid was not different among the mice homozygous, heterozygous or nullzygous (B10.BL allele) for the SAMP1 allele. Moreover, NZB/N, NFS/N, SJL/J, and NOD/ShiLtJ also have the Ogg1 p.R304W mutation. These results suggest that Ogg1 p.R304W alone is not sufficient to cause accelerated senescence and a short life span. We assume that the combination of Ogg1 p.R304W and Mbd4 p.D129N causes accelerated senescence. Both mutations were detected in the NOD/ShiLtJ strain, which is a type 1 diabetes model . Although NOD/ShiLtJ mice may live for only 6 to 8 months due to diabetes under normal food and water conditions , we cannot predicate these mutations to be essential for the accelerated-senescence phenotype of SAMP because the cause of death is different between SAMP and NOD/ShiLtJ strains. Nevertheless, mouse strains that possess Ogg1 p.R304W mutation are known for their pathologic phenotypes: NZB/N for autoimmune hemolytic anemia; SJL/J for reticulum cell sarcomas, in addition to NOD/ShiLtJ for type 1 diabetes [55, 56]. Somatic mutations have been implicated in various diseases, and the accumulation of such mutations is one of the most accepted theories to explain aging. The Ogg1 p.R304W mutation might partly contribute to the phenotypes of these mouse strains as well as to the accelerated-senescence phenotypes of SAMP strains.
In several SAMP strains, missense mutations were detected in the Prx, Ldb3, and Gja3 genes, which mutations have been found in various human degenerative diseases. The pathogenesis of myofibrillar myopathy and peripheral neurodegeneration has not been fully analyzed in SAMP strains. Age-related muscle atrophy and a decline in peripheral neuronal function are assumed to be a common phenomenon that probably occurs in the course of the senescence process [57, 58]. Nevertheless, genetic susceptibility to degeneration of skeletal muscle and peripheral neurons may be different among SAMP strains. Prx p.R167C and Ldb3 p.R473W mutations possibly contributed to the degenerative phenotypes of 3 of the SAMP strains in the course of the senescence process.
In the present study, the Gja3 p.S405P mutation was detected in 4 SAMP strains (SAMP3, SAMP6, SAMP10, and SAMP11), among which only the SAMP3 strain is reported to develop cataract . As a lack of reports of cataract in SAMP6, SAMP10, and SAMP11 does not indicate the actual lack of cataract, careful ophthalmologic examinations for cataracts in these 3 other SAMP strains may reveal a pathogenic association. Alternatively, because it is suggested that the pathogenic mechanism underlying the development of cataract in SAMP strains is different from that of murine hereditary cataract, which is generally regulated by single-gene mutations , the Gja3 mutation alone may not be sufficient to cause cataract. The SAMP3 strain may have additional mutations besides the Gja3 p.S405P mutation that are responsible for cataract.
The Il4ra p.S540fs frameshift mutation can explain the osteoporosis observed in the SAMP6 strain from the viewpoint of osteo-immunology. It is known that IL-4 signaling inhibits osteoclast differentiation by suppressing Th1 cytokines such as RANKL, TNF-α, and IL-1. In fact, Il4 gene knockout mice are sensitive to RANKL-induced bone resorption . A defect in Il4ra might thus enhance osteoclast differentiation due to dysregulation of Th1 cytokines. The Il4ra p.S540fs frameshift mutation can also explain the ulcerative colitis found in the SAMP6 strain. Although the true cause of ulcerative colitis remains unknown, abnormalities of the immune system are possibly related to its pathogenesis. Particularly, a high level of TNF-α was proposed to play an important role in disease progression . In SAMP6 mice, it is expected that up-regulation of TNF-α expression in the colon would occur due to activation of Th1 cells. Thus, both of these pathogenic phenotypes, osteoporosis and ulcerative colitis, may be ascribable to the defect in Il4ra in SAMP6.
We also detected the Aifm3 p.K582N mutation in the SAMP8/TaSlc mice, which display deficits in learning and memory. High oxidative stress derived from brain mitochondrial dysfunction is thought to be one of the causes of age-related neurodegeneration in SAMP8 animals. Actually, decreased activities of NADH-cytochrome c reductase are observed even in 4-week-old SAMP8 mice, suggesting crucial defects in maintenance of the respiratory chain . Aifm3 is likely to be related to mitochondrial maintenance, because it induces apoptosis in vitro and has an oxidoreductase domain, as is the case for Aifm1 , which plays roles in maintenance of the mitochondrial respiratory chain . However, the actual roles of Aifm3 in apoptosis in the senescence process and the actual substrates of the oxidoreductase remain unknown. Further investigations are necessary to examine whether the Aifm3 p.K582N contributes to deficits in learning and memory via dysfunction of brain mitochondria.
Overall, it seems that the combinations of different disease-causing mutations specific to each strain cause various degenerative diseases, which combinations are a cause of short life spans of SAMP strains as far as focusing on the mutations of the coding regions is concerned. Actually, it was reported earlier that the life spans of SAMP strains are susceptible to environmental conditions . These observations may be ascribable to the multifactorial nature of the short life span of SAMP unlike other progeroid mice whose life span is regulated by single gene mutation. de Magalhaes JP et al. also reported that the Gompertz mortality curve of the SAMP was not different from that of the SAMR prior to age 1 year despite the difference in age when 50% of mice died, suggesting that the life spans of the SAMP strains may not be related to aging per se. Nevertheless, we think that it is premature to conclude that SAMP strains are degenerative disease models rather than accelerated-senescence models because in vitro studies have shown that primary-cultured cells from several SAMP strains show accelerated senescence and higher oxidative stress and mitochondrial dysfunction than the SAMR1 strain [67–69].
Limitation of the present study
Whole-exome sequencing using 50-bp single-end reads on the SOLiD4 platform is able to detect only single or 2-base nucleotide variations and insertion/deletion. Because accelerated senescence and the various pathogenic phenotypes may not be explained completely by the nucleotide substitutions in the coding regions, we cannot ignore the possibility that other types of genetic variations are also involved in common accelerated-senescence phenotypes of SAMP strain. Fairfield et al. succeeded in identifying causative mutations in several ENU-induced mutants by exome sequencing, but failed to do so in several spontaneous disease models . They suggested that mutations responsible for spontaneous disease models might reside in the non-coding regions. Actually, it has been proven that most of the non-coding regions have some biochemical functions .
Carter et al. reported a 15-bp insertion mutation in the Fgf1 gene in SAMP10 , suggesting the involvement of a small structural variation in an exon of this gene. A long-read sequencing platform, which can generate over 200-bp fragments, would be required to detect them. It has been suggested that not only small structural variations in exons, but also large genomic structural variations such as copy number variations and gene translocations, contribute to the complex traits of humans . Furthermore, because complementary RNA probes are designed based on reference genome sequences, we were limited to find variants in comparison with the reference sequence. De novo assembly by whole genome sequencing or mate-pair library sequencing and comparative genomic hybridization (CGH) array analysis should be performed to detect these sequence variations.
In present study, we focused on only novel deleterious mutations that could be predicted by SIFT and PolyPhen-2. Although these bioinformatics tools are useful to narrow down the candidate mutations, a recent study indicated that SIFT and PolyPhen-2 show 63 and 79% correct prediction rates, respectively . In the future, functional analyses should be conducted to confirm whether the mutations that were predicted to be deleterious in the present study really affect the functions of these genes.
Our study using whole-exome sequencing provides a list of candidate mutations that are potentially linked with various pathogenic phenotypes. As was shown in Figure 3, 2 deleterious mutations in the DNA-repair genes, i.e., Ogg1 p.R304W and Mbd4 p.D129N, were commonly present among SAMP strains, which mutations would be expected to be involved in the genetic vulnerability to age-related diseases. Under such genetic backgrounds, deleterious mutations detected in each substrain may cause various pathogenic phenotypes. We revealed that only 7 SAMP-specific non-synonymous mutations were shared among substrains, although the mechanisms and development of accelerated senescence and short life span have been assumed to be the same among all of SAMP strains. Furthermore, several SAMP strains had deleterious mutations in the genes associated with hereditary diseases (e.g., Prx p.R167C, Ldb3 p.R473W and Gja3 p.S405P), which mutations have not been previously reported to occur in SAMP strains. These results suggest that comparison of age-related phenotypes among multiple SAMP strains and detailed histopathological reexamination are required. Phenotypic reports of specific SAMP strains have been biased by the researchers’ interests. The current exome sequence data will prompt us to scrutinize yet unnoticed pathological features. In addition to the exome database, construction of the comprehensive genome database of SAMP and SAMR strains will contribute not only to a better understanding of the fundamental aging process occurring in SAM strains but also to elucidation of the mechanisms of age-related diseases in humans as well as to the development of a more effective intervention against them.
Genomic DNA was extracted from the livers of 11 mouse strains, i.e., SAMP1/SkuSlc, SAMP3/SlcIdr, SAMP6/TaSlc, SAMP8/TaSlc, SAMP10/TaSlc, SAMP11/SlcIdr, SAMR1/SlcIdr, SAMR1/TaSlc, SAMR3B/SlcIdr, AKR/J and C57BL/6J strains. RNase treatment was performed to obtain a high-quality DNA library. All experimental procedures using laboratory animals were approved by the Animal Care and Use Committee of the Tokyo Metropolitan Institute of Gerontology, the Institute for Developmental Research of the Aichi Human Service Center, and by Shinshu University School of Medicine.
Targeted capture and next-generation sequencing
Target enrichment was performed by use of a SureSelectXT Mouse All Exon kit (Agilent Technologies, Santa Clara, California, US) optimized for the ABI SOLiD system and 3 μg of genomic DNA according to the manufacturer’s protocol. The kit is designed to enrich for 221,784 exons within 24,306 genes covering a total of 49.6 Mb genomic sequences. DNA was sheared by acoustic fragmentation (Covaris, Woburn, Massachusetts, US) and purified with an Agencourt AMPure XP kit (Beckman Coulter, Brea, California, US). The quality of the fragmentation and purification was assessed with an Agilent 2100 Bioanalyzer. The fragment ends were repaired and adaptors were ligated to the fragments (Agilent). The modified DNA library was purified by using the Agencourt AMPure XP kit, and amplified by PCR and captured by hybridization to biotinylated RNA library baits (Agilent). Captured DNA was purified with streptavidin-coated magnetic Dynal beads (Life Technologies, Carlsbad, California, US) and amplified with Barcoding Primer. The prepared exome library was pooled and subjected to emulsion PCR and sequenced on the SOLiD4 (Life Technologies) as single-end 50-bp reads. For each sample, 1 quad of a SOLiD sequencing slide was used.
Read mapping and variant analysis
Sequence reads were mapped to the reference mouse genome (UCSC mm9, NCBI build 37) by using Bioscope software version 1.3 (Life Technologies), which utilizes an iterative mapping approach. After removal of low-quality and duplicate reads, single nucleotide variants (SNVs) were detected with Avadis NGS software version1.3 (Strand Life Sciences, Bangalore, Karnataka, India). Avadis NGS performs SNV identification via an adapted version of the MAQ algorithm, which calculates the probability that the consensus genotype is incorrect by using a Bayesian statistical model with mapping quality, base quality and ploidy taken into consideration. We established criteria for SNV detection as a read coverage ≥ 2, and other parameters were set as default values. Detected SNVs were annotated for extracting non-synonymous and homozygous SNVs by using the Avadis NGS with UCSC transcript annotation. Moreover, we extracted novel SNVs by comparison with NCBI dbSNP build 128 and SNV data of 17 inbred strains of laboratory mice obtained by whole-genome sequencing. We compared filtered SNVs among all strains to explore the mutations that were commonly present among the SAMP strains but absent in the SAMR strains, AKR/J strain, and C57BL/6J strain. The unique mutations of each strain were also selected.
Interpretation of novel missense SNVs
To predict whether the candidate SNVs would have deleterious effects or not, we used 2 software programs, i.e., Sorting Intolerant from Tolerant amino acid substitutions (SIFT; J. Craig Venter Institute, San Diego, California, US, http://sift.jcvi.org/) and Polymorphism Phenotyping v2 (PolyPhen-2; Harvard University, Cambridge, Massachusetts, US, http://genetics.bwh.harvard.edu/pph2/). SIFT uses sequence homology to predict amino acid substitutions that will affect protein function, thus contributing to a disease . SIFT predicts substitutions with a score less than 0.05 as being “deleterious“ (Range: 0 to 1). PolyPhen-2 takes into account the physicochemical characteristics of the wild-type and mutated amino acid residue and the consequence of the amino acid change for the structural properties of the protein in addition to evolutional conservation . PolyPhen-2 generates a different scale of reported scores, with the corresponding predictions being “probably damaging” with a score larger than 0.85, “possibly damaging” with a score between 0.85 and 0.15,” and “benign” with a score less than 0.15. Because PolyPhen-2 considers only human protein sequences, the mouse SNVs were investigated in the context of human protein sequences.
Validating the candidate SNVs was performed by using the standard Sanger sequencing approach. Primers were designed to surround candidate SNVs by using Primer 3 version 4.0, and custom DNA oligos were ordered (Life Technologies; Operon Biotechnologies, Tokyo, Japan). Primer sequences are shown in Additional file 1: Tables S1-S2. PCR reactions were carried out in 10-μl reaction mixtures containing a 0.5 μM concentration of each primer, 0.2 mM dNTPs, 0.25U Ex Taq DNA Polymerase Hot-Start Version, 1.0 μl 10×Ex Taq Buffer (Takara Bio, Shiga, Japan), and 1 μl of extracted DNA. The amplification conditions were 1 cycle at 96°C for 5 min of denaturation, 40 cycles of 94°C for 30 s, 55-68°C for 45 s of annealing in proportion to the Tm value of each primer, and extension at 72°C for 45 s, followed by a final extension at 72°C for 10 min. PCR products were purified by using a MultiScreenHTS PCR 96-Well Plate (Millipore, Billerica, Massachusetts, US) for sequences. DNA templates were subjected to the sequencing reactions by using a BigDye Terminator version 3.1 Cycle Sequencing Kit (Life Technologies). The sequencing reaction solution contained 4 μl BigDye Terminator v3.1, 0.32 μM M13 forward primer, 1.75 μl 5×Sequence Buffer, and 2.0 μl PCR product in a final volume of 10 μl. PCR conditions were 1 cycle at 94°C of denaturation, 25 cycles of 94°C for 10 s, 50°C for 15 s and 3 min at 60°C, followed by cleaning of the reaction products by ethanol precipitation. The capillary electrophoresis sequencing was performed by using an ABI Prism 3130xl Genetic Analyzer (Life Technologies), and sequence data were analyzed with Sequencher version 4.2.2 (Gene Codes, Ann Arbor, Michigan, US).
Gene Ontology enrichment analysis
Gene Ontology enrichment analysis (GO analysis) was performed by using WebGestalt (http://bioinfo.vanderbilt.edu/webgestalt/) . The obtained p-values were adjusted by Benjamini-Hochberg multiple testing, and the significant level was established at p<0.05.
Exome data were deposited in DDBJ Sequence Read Archive (BioProject Accession Number: PRJDB37).
This work was supported in part by Grants-in-Aid for Scientific Research A-22240072, B-21390459, C-21590411 to MT) and a Grant-in-Aid for the Global COE (Sport Sciences for the Promotion of Active Life to Waseda University) from the Ministry of Education, Culture, Sports, Science, and Technology (to MT); by Grants-in-Aid for Young Scientists (A-21680050 and B-18700541 to NF) and a Grant-in-Aid for Exploratory Research (20650113 to NF) from the Ministry of Education, Culture, Sports, Science, and Technology; by grants for scientific research from The Takeda Science Foundation (to MT) and from The Uehara Memorial Foundation (to NF).
- Johnson FB, Sinclair DA, Guarente L: Molecular biology of aging. Cell. 1999, 96 (2): 291-302. 10.1016/S0092-8674(00)80567-X.Google Scholar
- Higuchi K: Genetic characterization of senescence-accelerated mouse (SAM). Exp Gerontol. 1997, 32 (1–2): 129-138.Google Scholar
- Takeda T, Hosokawa M, Higuchi K: Senescence-accelerated mouse (SAM): a novel murine model of senescence. Exp Gerontol. 1997, 32 (1–2): 105-109.Google Scholar
- Takeda T, Matsushita T, Kurozumi M, Takemura K, Higuchi K, Hosokawa M: Pathobiology of the senescence-accelerated mouse (SAM). Exp Gerontol. 1997, 32 (1–2): 117-127.Google Scholar
- Kitado H, Higuchi K, Takeda T: Molecular genetic characterization of the senescence-accelerated mouse (SAM) strains. J Gerontol. 1994, 49 (6): B247-B254. 10.1093/geronj/49.6.B247.Google Scholar
- Takeda T, Hosokawa M, Higuchi K: Senescence-accelerated mouse (SAM). A novel murine model of aging. The SAM model of senescence. Edited by: Takeda T. 1994, Amsterdam: Elsevier B. V, 15-Google Scholar
- Carter TA, Greenhall JA, Yoshida S, Fuchs S, Helton R, Swaroop A, Lockhart DJ, Barlow C: Mechanisms of aging in senescence-accelerated mice. Genome Biol. 2005, 6 (6): R48-10.1186/gb-2005-6-6-r48.PubMed CentralGoogle Scholar
- Higuchi K, Kitagawa K, Naiki H, Hanada K, Hosokawa M, Takeda T: Polymorphism of apolipoprotein A-II (apoA-II) among inbred strains of mice. Relationship between the molecular type of apoA-II and mouse senile amyloidosis. Biochem J. 1991, 279 (Pt 2): 427-433.PubMed CentralGoogle Scholar
- Nakanishi R, Shimizu M, Mori M, Akiyama H, Okudaira S, Otsuki B, Hashimoto M, Higuchi K, Hosokawa M, Tsuboyama T, Nakamura T: Secreted frizzled-related protein 4 is a negative regulator of peak BMD in SAMP6 mice. J Bone Miner Res. 2006, 21 (11): 1713-1721. 10.1359/jbmr.060719.Google Scholar
- Xia C, Higuchi K, Shimizu M, Matsushita T, Kogishi K, Wang J, Chiba T, Festing MF, Hosokawa M: Genetic typing of the senescence-accelerated mouse (SAM) strains with microsatellite markers. Mamm Genome. 1999, 10 (3): 235-238. 10.1007/s003359900979.Google Scholar
- Naiki H, Higuchi K, Shimada A, Takeda T, Nakakuki K: Genetic analysis of murine senile amyloidosis. Lab Invest. 1993, 68 (3): 332-337.Google Scholar
- Wang J, Wang W, Li R, Li Y, Tian G, Goodman L, Fan W, Zhang J, Li J, Guo Y, Feng B, Li H, Lu Y, Fang X, Liang H, Du Z, Li D, Zhao Y, Hu Y, Yang Z, Zheng H, Hellmann I, Inouye M, Pool J, Yi X, Zhao J, Duan J, Zhou Y, Qin J, Ma L: The diploid genome sequence of an Asian individual. Nature. 2008, 456 (7218): 60-65. 10.1038/nature07484.PubMed CentralGoogle Scholar
- Wheeler DA, Srinivasan M, Egholm M, Shen Y, Chen L, McGuire A, He W, Chen YJ, Makhijani V, Roth GT, Gomes X, Tartaro K, Niazi F, Turcotte CL, Irzyk GP, Lupski JR, Chinault C, Song XZ, Liu Y, Yuan Y, Nazareth L, Qin X, Muzny DM, Margulies M, Weinstock GM, Gibbs RA, Rothberg JM: The complete genome of an individual by massively parallel DNA sequencing. Nature. 2008, 452 (7189): 872-876. 10.1038/nature06884.Google Scholar
- Li Y, Vinckenbosch N, Tian G, Huerta-Sanchez E, Jiang T, Jiang H, Albrechtsen A, Andersen G, Cao H, Korneliussen T, Grarup N, Guo Y, Hellman I, Jin X, Li Q, Liu J, Liu X, Sparso T, Tang M, Wu H, Wu R, Yu C, Zheng H, Astrup A, Bolund L, Holmkvist J, Jorgensen T, Kristiansen K, Schmitz O, Schwartz TW: Resequencing of 200 human exomes identifies an excess of low-frequency non-synonymous coding variants. Nat Genet. 2010, 42 (11): 969-972. 10.1038/ng.680.Google Scholar
- Ng SB, Turner EH, Robertson PD, Flygare SD, Bigham AW, Lee C, Shaffer T, Wong M, Bhattacharjee A, Eichler EE, Bamshad M, Nickerson DA, Shendure J: Targeted capture and massively parallel sequencing of 12 human exomes. Nature. 2009, 461 (7261): 272-276. 10.1038/nature08250.PubMed CentralGoogle Scholar
- Bilguvar K, Ozturk AK, Louvi A, Kwan KY, Choi M, Tatli B, Yalnizoglu D, Tuysuz B, Caglayan AO, Gokben S, Kaymakcalan H, Barak T, Bakircioglu M, Yasuno K, Ho W, Sanders S, Zhu Y, Yilmaz S, Dincer A, Johnson MH, Bronen RA, Kocer N, Per H, Mane S, Pamir MN, Yalcinkaya C, Kumandas S, Topcu M, Ozmen M, Sestan N: Whole-exome sequencing identifies recessive WDR62 mutations in severe brain malformations. Nature. 2010, 467 (7312): 207-210. 10.1038/nature09327.PubMed CentralGoogle Scholar
- Ng SB, Buckingham KJ, Lee C, Bigham AW, Tabor HK, Dent KM, Huff CD, Shannon PT, Jabs EW, Nickerson DA, Shendure J, Bamshad MJ: Exome sequencing identifies the cause of a mendelian disorder. Nat Genet. 2010, 42 (1): 30-35. 10.1038/ng.499.PubMed CentralGoogle Scholar
- Feng BJ, Tavtigian SV, Southey MC, Goldgar DE: Design considerations for massively parallel sequencing studies of complex human disease. PLoS One. 2011, 6 (8): e23221-10.1371/journal.pone.0023221.PubMed CentralGoogle Scholar
- Jakovcevski M, Schachner M, Morellini F: Individual variability in the stress response of C57BL/6J male mice correlates with trait anxiety. Genes Brain Behav. 2008, 7 (2): 235-243. 10.1111/j.1601-183X.2007.00345.x.Google Scholar
- Watkins-Chow DE, Pavan WJ: Genomic copy number and expression variation within the C57BL/6J inbred mouse strain. Genome Res. 2008, 18 (1): 60-66.PubMed CentralGoogle Scholar
- Keane TM, Goodstadt L, Danecek P, White MA, Wong K, Yalcin B, Heger A, Agam A, Slater G, Goodson M, Furlotte NA, Eskin E, Nellaker C, Whitley H, Cleak J, Janowitz D, Hernandez-Pliego P, Edwards A, Belgard TG, Oliver PL, McIntyre RE, Bhomra A, Nicod J, Gan X, Yuan W, van der Weyden L, Steward CA, Bala S, Stalker J, Mott R: Mouse genomic variation and its effect on phenotypes and gene regulation. Nature. 2011, 477 (7364): 289-294. 10.1038/nature10413.PubMed CentralGoogle Scholar
- de Magalhaes JP, Toussaint O: GenAge: a genomic and proteomic network map of human ageing. FEBS Lett. 2004, 571 (1–3): 243-247.Google Scholar
- Mori M, Toyokuni S, Kondo S, Kasai H, Naiki H, Toichi E, Hosokawa M, Higuchi K: Spontaneous loss-of-function mutations of the 8-oxoguanine DNA glycosylase gene in mice and exploration of the possible implication of the gene in senescence. Free Radic Biol Med. 2001, 30 (10): 1130-1136. 10.1016/S0891-5849(01)00511-1.Google Scholar
- Nash HM, Bruner SD, Scharer OD, Kawate T, Addona TA, Spooner E, Lane WS, Verdine GL: Cloning of a yeast 8-oxoguanine DNA glycosylase reveals the existence of a base-excision DNA-repair protein superfamily. Curr Biol. 1996, 6 (8): 968-980. 10.1016/S0960-9822(02)00641-3.Google Scholar
- Thomas D, Scot AD, Barbey R, Padula M, Boiteux S: Inactivation of OGG1 increases the incidence of G . C-->T . A transversions in Saccharomyces cerevisiae: evidence for endogenous oxidative damage to DNA in eukaryotic cells. Mol Gen Genet. 1997, 254 (2): 171-178. 10.1007/s004380050405.Google Scholar
- Hendrich B, Hardeland U, Ng HH, Jiricny J, Bird A: The thymine glycosylase MBD4 can bind to the product of deamination at methylated CpG sites. Nature. 1999, 401 (6750): 301-304. 10.1038/45843.Google Scholar
- Makino S, Kunimoto K, Muraoka Y, Mizushima Y, Katagiri K, Tochino Y: Breeding of a non-obese, diabetic strain of mice. Jikken Dobutsu. 1980, 29 (1): 1-13.Google Scholar
- Threadgill DW, Miller DR, Churchill GA, de Villena FP: The collaborative cross: a recombinant inbred mouse population for the systems genetic era. ILAR J. 2011, 52 (1): 24-31. 10.1093/ilar.52.1.24.Google Scholar
- Takeda T: Senescence-accelerated mouse (SAM): a biogerontological resource in aging research. Neurobiol Aging. 1999, 20 (2): 105-110. 10.1016/S0197-4580(99)00008-1.Google Scholar
- Gillespie CS, Sherman DL, Blair GE, Brophy PJ: Periaxin, a novel protein of myelinating Schwann cells with a possible role in axonal ensheathment. Neuron. 1994, 12 (3): 497-508. 10.1016/0896-6273(94)90208-9.Google Scholar
- Guilbot A, Williams A, Ravise N, Verny C, Brice A, Sherman DL, Brophy PJ, LeGuern E, Delague V, Bareil C, Megarbane A, Claustres M: A mutation in periaxin is responsible for CMT4F, an autosomal recessive form of Charcot-Marie-Tooth disease. Hum Mol Genet. 2001, 10 (4): 415-421. 10.1093/hmg/10.4.415.Google Scholar
- Otagiri T, Sugai K, Kijima K, Arai H, Sawaishi Y, Shimohata M, Hayasaka K: Periaxin mutation in Japanese patients with Charcot-Marie-Tooth disease. J Hum Genet. 2006, 51 (7): 625-628. 10.1007/s10038-006-0408-3.Google Scholar
- Gillespie CS, Sherman DL, Fleetwood-Walker SM, Cottrell DF, Tait S, Garry EM, Wallace VC, Ure J, Griffiths IR, Smith A, Brophy PJ: Peripheral demyelination and neuropathic pain behavior in periaxin-deficient mice. Neuron. 2000, 26 (2): 523-531. 10.1016/S0896-6273(00)81184-8.Google Scholar
- Dingwall C, Sharnick SV, Laskey RA: A polypeptide domain that specifies migration of nucleoplasmin into the nucleus. Cell. 1982, 30 (2): 449-458. 10.1016/0092-8674(82)90242-2.Google Scholar
- Sherman DL, Brophy PJ: A tripartite nuclear localization signal in the PDZ-domain protein L-periaxin. J Biol Chem. 2000, 275 (7): 4537-4540. 10.1074/jbc.275.7.4537.Google Scholar
- Zhou Q, Ruiz-Lozano P, Martone ME, Chen J: Cypher, a striated muscle-restricted PDZ and LIM domain-containing protein, binds to alpha-actinin-2 and protein kinase C. J Biol Chem. 1999, 274 (28): 19807-19813. 10.1074/jbc.274.28.19807.Google Scholar
- Selcen D, Engel AG: Mutations in ZASP define a novel form of muscular dystrophy in humans. Ann Neurol. 2005, 57 (2): 269-276. 10.1002/ana.20376.Google Scholar
- Vatta M, Mohapatra B, Jimenez S, Sanchez X, Faulkner G, Perles Z, Sinagra G, Lin JH, Vu TM, Zhou Q, Bowles KR, Di Lenarda A, Schimmenti L, Fox M, Chrisco MA, Murphy RT, McKenna W, Elliott P, Bowles NE, Chen J, Valle G, Towbin JA: Mutations in Cypher/ZASP in patients with dilated cardiomyopathy and left ventricular non-compaction. J Am Coll Cardiol. 2003, 42 (11): 2014-2027. 10.1016/j.jacc.2003.10.021.Google Scholar
- Yamashita Y, Matsuura T, Shinmi J, Amakusa Y, Masuda A, Ito M, Kinoshita M, Furuya H, Abe K, Ibi T, Sahashi K, Ohno K: Four parameters increase the sensitivity and specificity of the exon array analysis and disclose 25 novel aberrantly spliced exons in myotonic dystrophy. J Hum Genet. 2012, 57 (6): 368-374. 10.1038/jhg.2012.37.Google Scholar
- Paul DL, Ebihara L, Takemoto LJ, Swenson KI, Goodenough DA: Connexin46, a novel lens gap junction protein, induces voltage-gated currents in nonjunctional plasma membrane of Xenopus oocytes. J Cell Biol. 1991, 115 (4): 1077-1089. 10.1083/jcb.115.4.1077.Google Scholar
- Bennett TM, Mackay DS, Knopf HL, Shiels A: A novel missense mutation in the gene for gap-junction protein alpha3 (GJA3) associated with autosomal dominant "nuclear punctate" cataracts linked to chromosome 13q. Mol Vis. 2004, 10: 376-382.Google Scholar
- Bennett TM, Shiels A: A recurrent missense mutation in GJA3 associated with autosomal dominant cataract linked to chromosome 13q. Mol Vis. 2011, 17: 2255-2262.PubMed CentralGoogle Scholar
- Matsushita M, Tsuboyama T, Kasai R, Okumura H, Yamamuro T, Higuchi K, Kohno A, Yonezu T, Utani A, Umezawa M, Takeda T: Age-related changes in bone mass in the senescence-accelerated mouse (SAM). SAM-R/3 and SAM-P/6 as new murine models for senile osteoporosis. Am J Pathol. 1986, 125 (2): 276-283.PubMed CentralGoogle Scholar
- Tanaka S, Shiokawa K, Miyaishi O: Effects of housing and nutritions condition on the reproductions of SAMR1, SAMP6 and SAMP8 at NILS aging farm. The Senescence-Accelerated Mouse (SAM): An Animal Model of Senescence. Edited by: Nomura Y. 2004, Amsterdam: Elsevier B. V, 167-173.Google Scholar
- Ishimi Y, Miyaura C, Jin CH, Akatsu T, Abe E, Nakamura Y, Yamaguchi A, Yoshiki S, Matsuda T, Hirano T: IL-6 is produced by osteoblasts and induces bone resorption. J Immunol. 1990, 145 (10): 3297-3303.Google Scholar
- Takahashi N, Udagawa N, Suda T: A new member of tumor necrosis factor ligand family, ODF/OPGL/TRANCE/RANKL, regulates osteoclast differentiation and function. Biochem Biophys Res Commun. 1999, 256 (3): 449-455. 10.1006/bbrc.1999.0252.Google Scholar
- Thomson BM, Mundy GR, Chambers TJ: Tumor necrosis factors alpha and beta induce osteoblastic cells to stimulate osteoclastic bone resorption. J Immunol. 1987, 138 (3): 775-779.Google Scholar
- Thomson BM, Saklatvala J, Chambers TJ: Osteoblasts mediate interleukin 1 stimulation of bone resorption by rat osteoclasts. J Exp Med. 1986, 164 (1): 104-112. 10.1084/jem.164.1.104.Google Scholar
- Korycka J, Lach A, Heger E, Boguslawska DM, Wolny M, Toporkiewicz M, Augoff K, Korzeniewski J, Sikorski AF: Human DHHC proteins: a spotlight on the hidden player of palmitoylation. Eur J Cell Biol. 2011, 91 (2): 107-117.Google Scholar
- Saleem AN, Chen YH, Baek HJ, Hsiao YW, Huang HW, Kao HJ, Liu KM, Shen LF, Song IW, Tu CP, Wu JY, Kikuchi T, Justice MJ, Yen JJ, Chen YT: Mice with alopecia, osteoporosis, and systemic amyloidosis due to mutation in Zdhhc13, a gene coding for palmitoyl acyltransferase. PLoS Genet. 2010, 6 (6): e1000985-10.1371/journal.pgen.1000985.PubMed CentralGoogle Scholar
- Leong WF, Zhou T, Lim GL, Li B: Protein palmitoylation regulates osteoblast differentiation through BMP-induced osterix expression. PLoS One. 2009, 4 (1): e4135-10.1371/journal.pone.0004135.PubMed CentralGoogle Scholar
- Miyamoto M, Kiyota Y, Nishiyama M, Nagaoka A: Senescence-accelerated mouse (SAM): age-related reduced anxiety-like behavior in the SAM-P/8 strain. Physiol Behav. 1992, 51 (5): 979-985. 10.1016/0031-9384(92)90081-C.Google Scholar
- Miyamoto M, Kiyota Y, Yamazaki N, Nagaoka A, Matsuo T, Nagawa Y, Takeda T: Age-related changes in learning and memory in the senescence-accelerated mouse (SAM). Physiol Behav. 1986, 38 (3): 399-406. 10.1016/0031-9384(86)90112-5.Google Scholar
- Xie Q, Lin T, Zhang Y, Zheng J, Bonanno JA: Molecular cloning and characterization of a human AIF-like gene with ability to induce apoptosis. J Biol Chem. 2005, 280 (20): 19673-19681. 10.1074/jbc.M409517200.Google Scholar
- Carswell EA, Wanebo HJ, Old LJ, Boyse EA: Immunogenic properties of reticulum cell sarcomas of SJL/J mice. J Natl Cancer Inst. 1970, 44 (6): 1281-1288.Google Scholar
- Holmes MC, Burnet FM: The Natural History of Autoimmune Disease in Nzb Mice. A Comparison with the Pattern of Human Autoimmune Manifestations. Ann Intern Med. 1963, 59: 265-276. 10.7326/0003-4819-59-3-265.Google Scholar
- Frontera WR, Hughes VA, Fielding RA, Fiatarone MA, Evans WJ, Roubenoff R: Aging of skeletal muscle: a 12-yr longitudinal study. J Appl Physiol. 2000, 88 (4): 1321-1326.Google Scholar
- Verdu E, Ceballos D, Vilches JJ, Navarro X: Influence of aging on peripheral nerve function and regeneration. J Peripher Nerv Syst. 2000, 5 (4): 191-208. 10.1046/j.1529-8027.2000.00026.x.Google Scholar
- Hosokawa M, Takeshita S, Higuchi K, Shimizu K, Irino M, Toda K, Honma A, Matsumura A, Yasuhira K, Takeda T: Cataract and other ophthalmic lesions in senescence accelerated mouse (SAM). Morphology and incidence of senescence associated ophthalmic changes in mice. Exp Eye Res. 1984, 38 (2): 105-114. 10.1016/0014-4835(84)90095-2.Google Scholar
- Nishimoto H, Uga S, Miyata M, Ishikawa S, Yamashita K: Morphological study of the cataractous lens of the senescence accelerated mouse. Graefes Arch Clin Exp Ophthalmol. 1993, 231 (12): 722-728. 10.1007/BF00919288.Google Scholar
- Mangashetti LS, Khapli SM, Wani MR: IL-4 inhibits bone-resorbing activity of mature osteoclasts by affecting NF-kappa B and Ca2+ signaling. J Immunol. 2005, 175 (2): 917-925.Google Scholar
- Sands BE, Kaplan GG: The role of TNFalpha in ulcerative colitis. J Clin Pharmacol. 2007, 47 (8): 930-941. 10.1177/0091270007301623.Google Scholar
- Fujibayashi Y, Yamamoto S, Waki A, Konishi J, Yonekura Y: Increased mitochondrial DNA deletion in the brain of SAMP8, a mouse model for spontaneous oxidative stress brain. Neurosci Lett. 1998, 254 (2): 109-112. 10.1016/S0304-3940(98)00667-3.Google Scholar
- Cheung EC, Joza N, Steenaart NA, McClellan KA, Neuspiel M, McNamara S, MacLaurin JG, Rippstein P, Park DS, Shore GC, McBride HM, Penninger JM, Slack RS: Dissociating the dual roles of apoptosis-inducing factor in maintaining mitochondrial structure and apoptosis. EMBO J. 2006, 25 (17): 4061-4073. 10.1038/sj.emboj.7601276.PubMed CentralGoogle Scholar
- Takeda T: Effects of environment on life span and pathobiological phenotypes in senescence-accelerated mice. The Senescence-Accelerated Mouse (SAM): An Animal Model of Senescence. Edited by: Nomura Y. 2004, Amsterdam: Elsevier B. V, 3-12.Google Scholar
- de Magalhaes JP, Cabral JA, Magalhaes D: The influence of genes on the aging process of mice: a statistical assessment of the genetics of aging. Genetics. 2005, 169 (1): 265-274.PubMed CentralGoogle Scholar
- Chiba Y, Yamashita Y, Ueno M, Fujisawa H, Hirayoshi K, Hohmura K, Tomimoto H, Akiguchi I, Satoh M, Shimada A, Hosokawa M: Cultured murine dermal fibroblast-like cells from senescence-accelerated mice as in vitro models for higher oxidative stress due to mitochondrial alterations. J Gerontol A Biol Sci Med Sci. 2005, 60 (9): 1087-1098. 10.1093/gerona/60.9.1087.Google Scholar
- Hosokawa M, Ashida Y, Nishikawa T, Takeda T: Accelerated aging of dermal fibroblast-like cells from senescence-accelerated mouse (SAM). 1. Acceleration of population aging in vitro. Mech Ageing Dev. 1994, 74 (1–2): 65-77.Google Scholar
- Lecka-Czernik B, Moerman EJ, Shmookler Reis RJ, Lipschitz DA: Cellular and molecular biomarkers indicate precocious in vitro senescence in fibroblasts from SAMP6 mice. Evidence supporting a murine model of premature senescence and osteopenia. J Gerontol A Biol Sci Med Sci. 1997, 52 (6): B331-Google Scholar
- Fairfield H, Gilbert GJ, Barter M, Corrigan RR, Curtain M, Ding Y, D'Ascenzo M, Gerhardt DJ, He C, Huang W, Richmond T, Rowe L, Probst FJ, Bergstrom DE, Murray SA, Bult C, Richardson J, Kile BT, Gut I, Hager J, Sigurdsson S, Mauceli E, Di Palma F, Lindblad-Toh K, Cunningham ML, Cox TC, Justice MJ, Spector MS, Lowe SW, Albert T: Mutation discovery in mice by whole exome sequencing. Genome Biol. 2011, 12 (9): R86-10.1186/gb-2011-12-9-r86.PubMed CentralGoogle Scholar
- Dunham I, Kundaje A, Aldred SF, Collins PJ, Davis CA, Doyle F, Epstein CB, Frietze S, Harrow J, Kaul R, Khatun J, Lajoie BR, Landt SG, Lee BK, Pauli F, Rosenbloom KR, Sabo P, Safi A, Sanyal A, Shoresh N, Simon JM, Song L, Trinklein ND, Altshuler RC, Birney E, Brown JB, Cheng C, Djebali S, Dong X, Ernst J: An integrated encyclopedia of DNA elements in the human genome. Nature. 2012, 489 (7414): 57-74. 10.1038/nature11247.Google Scholar
- Sebat J, Lakshmi B, Troge J, Alexander J, Young J, Lundin P, Maner S, Massa H, Walker M, Chi M, Navin N, Lucito R, Healy J, Hicks J, Ye K, Reiner A, Gilliam TC, Trask B, Patterson N, Zetterberg A, Wigler M: Large-scale copy number polymorphism in the human genome. Science. 2004, 305 (5683): 525-528. 10.1126/science.1098918.Google Scholar
- Gray VE, Kukurba KR, Kumar S: Performance of computational tools in evaluating the functional impact of laboratory-induced amino acid mutations. Bioinformatics. 2012, 28 (16): 2093-2096. 10.1093/bioinformatics/bts336.PubMed CentralGoogle Scholar
- Ng PC, Henikoff S: SIFT: Predicting amino acid changes that affect protein function. Nucleic Acids Res. 2003, 31 (13): 3812-3814. 10.1093/nar/gkg509.PubMed CentralGoogle Scholar
- Ramensky V, Bork P, Sunyaev S: Human non-synonymous SNPs: server and survey. Nucleic Acids Res. 2002, 30 (17): 3894-3900. 10.1093/nar/gkf493.PubMed CentralGoogle Scholar
- Zhang B, Kirov S, Snoddy J: WebGestalt: an integrated system for exploring gene sets in various biological contexts. Nucleic Acids Res. 2005, 33 (Web Server issue): W741-W748.PubMed CentralGoogle Scholar
- Sievers F, Wilm A, Dineen D, Gibson TJ, Karplus K, Li W, Lopez R, McWilliam H, Remmert M, Soding J, Thompson JD, Higgins DG: Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol. 2011, 7: 539-PubMed CentralGoogle Scholar
- Hosokawa T, Hosono M, Hanada K, Aoike A, Kawai K, Takeda T: Immune responses in newly developed short-lived SAM mice. Selectively impaired T-helper cell activity in in vitro antibody response. Immunology. 1987, 62 (3): 425-429.PubMed CentralGoogle Scholar
- Hosokawa T, Hosono M, Higuchi K, Aoike A, Kawai K, Takeda T: Immune responses in newly developed short-lived SAM mice. I. Age-associated early decline in immune activities of cultured spleen cells. Immunology. 1987, 62 (3): 419-423.PubMed CentralGoogle Scholar
- Kurozumi M, Matsushita T, Hosokawa M, Takeda T: Age-related changes in lung structure and function in the senescence-accelerated mouse (SAM): SAM-P/1 as a new murine model of senile hyperinflation of lung. Am J Respir Crit Care Med. 1994, 149 (3 Pt 1): 776-782.Google Scholar
- Ogawa H: Renal lesions of the senescence accelerated mouse (SAM), with special emphasis on senility. Nihon Jinzo Gakkai Shi. 1988, 30 (9): 1063-1065.Google Scholar
- Takeshita S, Hosokawa M, Irino M, Higuchi K, Shimizu K, Yasuhira K, Takeda T: Spontaneous age-associated amyloidosis in senescence-accelerated mouse (SAM). Mech Ageing Dev. 1982, 20 (1): 13-23. 10.1016/0047-6374(82)90070-7.Google Scholar
- Stanton H, Rogerson FM, East CJ, Golub SB, Lawlor KE, Meeker CT, Little CB, Last K, Farmer PJ, Campbell IK, Fourie AM, Fosang AJ: ADAMTS5 is the major aggrecanase in mouse cartilage in vivo and in vitro. Nature. 2005, 434 (7033): 648-652. 10.1038/nature03417.Google Scholar
- Malfait AM, Liu RQ, Ijiri K, Komiya S, Tortorella MD: Inhibition of ADAM-TS4 and ADAM-TS5 prevents aggrecan degradation in osteoarthritic cartilage. J Biol Chem. 2002, 277 (25): 22201-22208. 10.1074/jbc.M200431200.Google Scholar
- Li J, Anemaet W, Diaz MA, Buchanan S, Tortorella M, Malfait AM, Mikecz K, Sandy JD, Plaas A: Knockout of ADAMTS5 does not eliminate cartilage aggrecanase activity but abrogates joint fibrosis and promotes cartilage aggrecan deposition in murine osteoarthritis models. J Orthop Res. 2011, 29 (4): 516-522. 10.1002/jor.21215.Google Scholar
- Chen WH, Hosokawa M, Tsuboyama T, Ono T, Iizuka T, Takeda T: Age-related changes in the temporomandibular joint of the senescence accelerated mouse. SAM-P/3 as a new murine model of degenerative joint disease. Am J Pathol. 1989, 135 (2): 379-385.PubMed CentralGoogle Scholar
- Kozyrev SV, Abelson AK, Wojcik J, Zaghlool A, Linga Reddy MV, Sanchez E, Gunnarsson I, Svenungsson E, Sturfelt G, Jonsen A, Truedsson L, Pons-Estel BA, Witte T, D'Alfonso S, Barizzone N, Danieli MG, Gutierrez C, Suarez A, Junker P, Laustrup H, Gonzalez-Escribano MF, Martin J, Abderrahim H, Alarcon-Riquelme ME: Functional variants in the B-cell gene BANK1 are associated with systemic lupus erythematosus. Nat Genet. 2008, 40 (2): 211-216. 10.1038/ng.79.Google Scholar
- Orozco G, Abelson AK, Gonzalez-Gay MA, Balsa A, Pascual-Salcedo D, Garcia A, Fernandez-Gutierrez B, Petersson I, Pons-Estel B, Eimon A, Paira S, Scherbarth HR, Alarcon-Riquelme M, Martin J: Study of functional variants of the BANK1 gene in rheumatoid arthritis. Arthritis Rheum. 2009, 60 (2): 372-379. 10.1002/art.24244.Google Scholar
- Shimada A, Ohta A, Akiguchi I, Takeda T: Inbred SAM-P/10 as a mouse model of spontaneous, inherited brain atrophy. J Neuropathol Exp Neurol. 1992, 51 (4): 440-450. 10.1097/00005072-199207000-00006.Google Scholar
- Shimada A, Ohta A, Akiguchi I, Takeda T: Age-related deterioration in conditional avoidance task in the SAM-P/10 mouse, an animal model of spontaneous brain atrophy. Brain Res. 1993, 608 (2): 266-272. 10.1016/0006-8993(93)91467-7.Google Scholar
- Chang MS, Lowe DG, Lewis M, Hellmiss R, Chen E, Goeddel DV: Differential activation by atrial and brain natriuretic peptides of two different receptor guanylate cyclases. Nature. 1989, 341 (6237): 68-72. 10.1038/341068a0.Google Scholar
- de Bold AJ: Atrial natriuretic factor: a hormone produced by the heart. Science. 1985, 230 (4727): 767-770. 10.1126/science.2932797.Google Scholar
- Sudoh T, Kangawa K, Minamino N, Matsuo H: A new natriuretic peptide in porcine brain. Nature. 1988, 332 (6159): 78-81. 10.1038/332078a0.Google Scholar
- Simonnet G, Allard M, Legendre P, Gabrion J, Vincent JD: Characteristics and specific localization of receptors for atrial natriuretic peptides at non-neuronal cells in cultured mouse spinal cord cells. Neuroscience. 1989, 29 (1): 189-199. 10.1016/0306-4522(89)90342-4.Google Scholar
- Teoh R, Kum W, Cockram CS, Young JD, Nicholls MG: Mouse astrocytes possess specific ANP receptors which are linked to cGMP production. Clin Exp Pharmacol Physiol. 1989, 16 (4): 323-327. 10.1111/j.1440-1681.1989.tb01566.x.Google Scholar
- Hasegawa-Ishii S, Takei S, Inaba M, Umegaki H, Chiba Y, Furukawa A, Kawamura N, Hosokawa M, Shimada A: Defects in cytokine-mediated neuroprotective glial responses to excitotoxic hippocampal injury in senescence-accelerated mouse. Brain Behav Immun. 2011, 25 (1): 83-100. 10.1016/j.bbi.2010.08.006.Google Scholar
- Zhu BH, Ueno M, Matsushita T, Fujisawa H, Seriu N, Nishikawa T, Nishimura Y, Hosokawa M: Effects of aging and blood pressure on the structure of the thoracic aorta in SAM mice: a model of age-associated degenerative vascular changes. Exp Gerontol. 2001, 36 (1): 111-124. 10.1016/S0531-5565(00)00179-0.Google Scholar
- Beyer EC, Paul DL, Goodenough DA: Connexin43: a protein from rat heart homologous to a gap junction protein from liver. J Cell Biol. 1987, 105 (6 Pt1): 2621-2629.Google Scholar
- Beyer EC, Kistler J, Paul DL, Goodenough DA: Antisera directed against connexin43 peptides react with a 43-kD protein localized to gap junctions in myocardium and other tissues. J Cell Biol. 1989, 108 (2): 595-605. 10.1083/jcb.108.2.595.Google Scholar
- Britz-Cunningham SH, Shah MM, Zuppan CW, Fletcher WH: Mutations of the Connexin43 gap-junction gene in patients with heart malformations and defects of laterality. N Engl J Med. 1995, 332 (20): 1323-1329. 10.1056/NEJM199505183322002.Google Scholar
- Dasgupta C, Martinez AM, Zuppan CW, Shah MM, Bailey LL, Fletcher WH: Identification of connexin43 (alpha1) gap junction gene mutations in patients with hypoplastic left heart syndrome by denaturing gradient gel electrophoresis (DGGE). Mutat Res. 2001, 479 (1–2): 173-186.Google Scholar
- Blackburn JP, Connat JL, Severs NJ, Green CR: Connexin43 gap junction levels during development of the thoracic aorta are temporally correlated with elastic laminae deposition and increased blood pressure. Cell Biol Int. 1997, 21 (2): 87-97. 10.1006/cbir.1996.0122.Google Scholar
- Little TL, Beyer EC, Duling BR: Connexin 43 and connexin 40 gap junctional proteins are present in arteriolar smooth muscle and endothelium in vivo. Am J Physiol. 1995, 268 (2 Pt 2): H729-H739.Google Scholar
- Liao Y, Regan CP, Manabe I, Owens GK, Day KH, Damon DN, Duling BR: Smooth muscle-targeted knockout of connexin43 enhances neointimal formation in response to vascular injury. Arterioscler Thromb Vasc Biol. 2007, 27 (5): 1037-1042. 10.1161/ATVBAHA.106.137182.Google Scholar
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