Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2012 Jun 25.
Published in final edited form as: Eur J Neurosci. 2010 Aug;32(4):523–537. doi: 10.1111/j.1460-9568.2010.07316.x

Identification of a Chr 11 quantitative trait locus that modulates proliferation in the rostral migratory stream of the adult mouse brain

Anna Poon 1,†, Zhiyou Li 2,†, Gregory W Wolfe 3, Lu Lu 2, Robert W Williams 2, Nancy L Hayes 4, Richard S Nowakowski 4, Daniel Goldowitz 1
PMCID: PMC3382016  NIHMSID: NIHMS210978  PMID: 20718853

Abstract

Neuron production takes place continuously in the rostral migratory stream (RMS) of the adult mammalian brain. The molecular mechanisms that regulate progenitor cell division and differentiation in the RMS remain largely unknown. Here, we surveyed the mouse genome in an unbiased manner to identify candidate gene loci that regulate proliferation in the adult RMS. We quantified neurogenesis in adult C57BL/6J and A/J mice and 27 recombinant inbred lines derived from those parental strains. We showed that the A/J RMS had greater numbers of bromodeoxyuridine-labeled cells than that of C57BL/6J mice with similar cell cycle parameters, indicating that the differences in the number of bromodeoxyuridine-positive cells reflected the number of proliferating cells between the strains. AXB and BXA recombinant inbred strains demonstrated even greater variation in the numbers of proliferating cells. Genome-wide mapping of this trait revealed that chromosome 11 harbors a significant quantitative trait locus at 116.75 ± 0.75Mb that affects cell proliferation in the adult RMS. The genomic regions that influence RMS proliferation did not overlap with genomic regions regulating proliferation in the adult subgraular zone of the hippocampal dentate gyrus. On the contrary, a different, suggestive locus that modulate cell proliferation in the subgranular zone was mapped to chromosome 3 at 102 ± 7 Mb. A subset of genes in the chromosome 11 quantitative trait locus region is associated with neurogenesis and cell proliferation. Our findings provide new insights into the genetic control of neural proliferation and an excellent starting point to identify genes critical to this process.

Keywords: olfactory bulb neurogenesis, neural progenitor, bromodeoxyuridine, cell cycle, recombinant inbred mice

Introduction

Adult neurogenesis is a process of continually adding new neurons to specific regions of the brain throughout life of many vertebrate species including human beings. The olfactory bulb (OB) is one of the best studied brain structures that receive daily supplies of new neurons. Specific types of interneurons, namely granule and periglomerular cells are produced by rapidly dividing neural precursors called neuroblasts in the rostral migratory stream (RMS), a rostral extension of the subventricular zone (SVZ) of the lateral ventricle (Zhao et al., 2008). Neuroblasts in the RMS maintain their ability to proliferate, but once they reach the OB, they differentiate into interneurons. Over 30,000 neuroblasts are found to migrate tangentially along the mouse RMS on a daily basis (Lois & Alvarez-Buylla, 1994). Neurogenesis in the RMS is important for the structural integrity of the OB and has been functionally implicated in odor memory formation and odor discrimination in rodents (Imayoshi et al., 2008; Gheusi et al., 2000; Rochefort et al., 2002).

There is an emerging picture of the genetic regulation of neural proliferation during OB neurogenesis. For instance, using targeted gene-driven approaches, knockouts of querkopf (Qkf) (Merson et al., 2006), ventral anterior homeobox (Vax1) (Soria et al., 2004) and the orphan nuclear receptor tailless (Tlx/Nr2e1) (Liu et al., 2008) all exhibited significant reduction of neuroblasts in the RMS and resulted substantially less interneurons in the OB as compared with their wild types. Studies have also shown that neural proliferation in the adult mouse brain is differentially influenced by the genetic background of several mouse strains (Lee et al., 2003; Kempermann et al., 2002), leading us to suspect that a considerable portion of this variance is modulated by polymorphisms and their associated genes.

The present study aims to identify genetic loci and candidate genes that are responsible for the natural variation in proliferation within the RMS. We have taken a phenotype-driven approach whereby we identified significant differences in the RMS proliferative capacity between two inbred mouse strains, C57/6J and A/J, based upon a quantitative analysis of bromodeoxyuridine (BrdU)-immunoreactive cells. We also examined cell cycle parameters between the two strains and found no significant differences. We then probed for the genetic basis of variation in RMS proliferative cell number using a series of recombinant inbred (RI) mice derived from the parental A/J and C57BL/6J strains to map quantitative trait loci (QTL) responsible for adult neurogenesis. We found that chromosome 11 harbors a QTL that significantly modulates cell proliferation in the adult RMS but not proliferation in another major site of neurogenesis called the subgranular zone of the dentate gyrus. Our findings provide insights into the complex genetic architecture of neural proliferation in the adult mammalian brain.

Materials and methods

Animals

Two inbred mouse strains, A/J and C57BL/6J, and a set of twenty-seven AXB/BXA RI strains (derived from reciprocal intercrossing C57BL/6J and A/J followed by inbreeding progeny for ≥ 20 generations) were obtained from The Jackson Laboratory (Bar Harbor, ME, USA). Male and female mice were kept under a 12 h dark: 12 h light cycle and were given ad libitum access to food and water. Animals studied were between 60–150 days old (n=118), but the majority of them (98 out of the 118) were 80±20 days old. All experimental procedures were conducted under an Institutional Animal Care and Use Committee (IACUC)-approved protocol from the University of Tennessee as well as the Canadian Council on Animal Care (CCAC)- approved protocol from the University of British Columbia.

BrdU administration and tissue preparation

The thymidine analog, BrdU, which is actively incorporated into the S phase of dividing cells, was used to label and quantify constitutively proliferating cells in the RMS of C57BL/6J, A/J, and the AXB/BXA RI strains. All mice received a single intraperitoneal injection of BrdU (Sigma-Aldrich) at a dosage of 50 mg BrdU/kg of body weight using a stock solution of 5 mg BrdU/ml in 0.9% NaCl containing 0.007 N NaOH. An hour later, animals were anesthetized with an overdose of Avertin (Sigma-Aldrich; 0.2ml/10g body weight), and perfused transcardially with 0.1M phosphate buffer (PB; pH ~7.2) followed by a solution of 95% alcohol:acetic acid (3:1). Brains were removed from the skull and postfixed the same acid alcohol solution at 4°C overnight before being bisected and processed for paraffin embedding. Brains were dehydrated through a graded alcohol series and xylenes, and then infiltrated with paraffin (Paraplast Plus). Each brain hemisphere was embedded separately, serially sectioned in the sagittal plane at 8 µm, and then mounted on Superfrost/Plus slides.

Cumulative BrdU Labeling for Cell Cycle Analysis

BrdU was also used to determine the cell cycle length of rapidly dividing cells in the RMS by adopting the cumulative BrdU labeling protocol developed by Nowakowski et al. (1989). BrdU was administered to a new batch of 2–3 months old male C57BL/6J and A/J mice (5mg/ml BrdU in 0.9% NaCl and 0.007N NaOH ; 50 mg/kg of body weight) every two hours for a total period of 10 h to ensure that every dividing cell entering the S-phase has the chance to be labeled. Animals were anesthetized with Avertin and perfused transcardially at 0.5, 2.5, 4.5, 6.5, 8.5, 10.5 h after the first BrdU injection. A total of 60 animals were used for the cell cycle analysis (5 A/Js and 5 C57BL/6Js at each time point). Brain tissues were prepared as described above.

Anti-BrdU immunohistochemistry

Sections were deparaffinized in xylenes, rehydrated in a graded series of alcohol, treated with 1N HCl for 30 min at 37° C to denature DNA, rinsed with 0.1 M PBS, treated with 1% H2O2 in PBS to block endogenous peroxidase, and washed for 5 min in 0.1M PBST. Sections were then treated with incubation buffer (30% BSA 1:100, NGS 1:20, NaN3 1:100, in 0.1M PBST) for 20 min before incubating them with mouse anti-BrdU monoclonal antibody (diluted 1:200 in incubation buffer; BD Biosciences, Mississauga, ON, Canada) overnight at room temperature. The next day, sections were rinsed with 0.1M PBST, incubated in biotinylated horse anti-mouse IgG (1:200, Vector Laboratories, Burlingame, CA, USA) for1 h, and rinsed again with 0.1M PBST. Tissue sections were then treated with solutions from the VECTASTAIN Elite ABC kit (Vector Laboratories, Burlingame, CA, USA) according to supplier’s instructions for 30 min at room temperature followed by 0.1M and 0.001 M PB washes. Immunoreactivity was detected using 3, 3’-Diaminobenzidine (DAB; Sigma-Aldrich) at 25mg/50mL in 0.1 M PB with 0.004% H2O2. Sections were thoroughly rinsed with dH20, dehydrated, and then coverslipped.

Quantification of proliferative cells in the AXB/BXA panel

To determine the number of BrdU-positive cells in the RMS, we first located the RMS by staining every 10th section throughout the left hemisphere with anti-BrdU, and then identified the single sagittal section within the 10-series that had the greatest representation of the RMS for analysis. Distribution of 1 h-labeled BrdU cells was found to be highly localized in the RMS which begins at the rostral tip of the lateral ventricle and terminates at the caudal end of the olfactory bulb (Fig. 1). The linear density of BrdU-positive cells per millimeter of RMS length was calculated from a single section that contained the most intact RMS exhibiting the stereotypical trajectory of proliferating cells en route to the OB. BrdU-immunoreactive cells in the RMS of this optimal section were counted under brightfield illumination and with the aid of a 20 × objective (Zeiss 200M Axiovert inverted microscope equipped with an Axiovision 4.6 software). The RMS length was measured using NIH ImageJ (version 1.42) software. Linear density from 1 hour BrdU labeling was systematically determined for A/J, C57BL/6J, and their RI strains and it was expressed as mean ± standard error of mean (SEM) for each strain. Another counting approach adapted from Lee et al. (2003) was used where we counted the number of BrdU-positive cells in every 10th immunostained sections (80µm intervals) throughout the entire medial to lateral extent of the RMS. The total number of labeled cells was calculated for 20 randomly selected animals and this value is highly correlated with the linear density (R= 0.88; P < 0.0001; see Supplementary material, Fig. S1), thus demonstrating the effectiveness of our single best-section quantification method.

FIG. 1.

FIG. 1

Open in a new tab

Distribution of 1 hour- labeled BrdU+ cells was highly localized in the rostral migratory stream (RMS). In this study, every 10th sagittal section (8µm thick), taken medial to lateral of the left hemisphere was subjected to anti-BrdU immunohistochemistry. Stained section shown in (A) contains the most complete RMS out of all the sections surveyed from an exemplary adult AXB24 mouse brain and was used to calculate the linear density (BrdU+ cells/mm). (B) A higher magnification image of BrdU+ cells in the RMS. (C) Schematic representation of the stained sagittal section in (A) highlights the location of the RMS relative to the dentate gyrus (DG), lateral ventricle (LV), and olfactory bulb (OB).

Animals used for analysis of BrdU-labeling in the RMS were also used to examine the proliferative activities in another neurogenic site, the subgranular zone (SGZ) of the hippocampal dentate gyrus. We quantified BrdU-positive cells in the SGZ, which is located at the interface between hilus and the granular layer of the dentate gyrus (DG), and this proliferative layer can be easily visualized by cresyl violet (CV) stain under a 40× objective (Kempermann et al. 2003). Counts began at the first appearance of the dentate hilus and dorsal and ventral granule cell layers and continued, in every 10th sagittal section, throughout the dorsal hippocampus and stopped where the dorsal and ventral components of the hippocampus merge. Data are expressed as the total number of BrdU-positive cells ± SEM. The same investigator performed all the quantification of the RMS and SGZ to reduce inter-observer variation in cell counting parameters. Also, the identity of the mice from which the sections were generated was unknown to the investigator during the data collection phase.

Cell cycle analysis of the proliferative populations in the RMS

We used the cumulative BrdU labeling protocol to measure and compare the lengths of the cell cycle and S phase of the rapidly dividing cell populations in the RMS of C57BL/6J and A/J (Nowakowski et al., 1989). Administrations of BrdU and tissue preparation were as described above. Consecutive sections were cut at 8µm thickness, stained with anti-BrdU, and counterstained with CV. Using a 40× objective, we determined the labeling index (LIt) - the ratio of BrdU positive cells to the total RMS cell population at a given time (t) - in brains obtained from animals sacrificed at t=0.5, 2.5, 4.5, 6.5, 8.5, 10.5 hours after the first BrdU injection. Since the RMS is a long compact cellular architecture, we estimated the total cell population by selecting four representative segments along the course of each RMS (two from the vertical arm, one from the RMS elbow, and one from the horizontal arm depicted in Supplementary material, Fig. S2), counted all cells within these segments and measured the corresponding area (mean value of each segment is 4500um2) to obtain the estimated cell density of the RMS. RMS lengths and areas were measured using AnalySIS Opti Version 3.3.776 software (Soft Image System). The density was then multiplied by the total RMS area to estimate the total cells in an RMS. Once the LIs at every time point are calculated for each genotype, the average LI (y axis) is plotted against the time after the first BrdU injection (x axis). We used the equation, LI0=GF*Ts/Tc, to calculate the length of the S phase (Ts) and the length of the cell cycle (Tc) (Nowakowski et al., 1989) where LI0 is the labeling index at the time of the first BrdU administration (t = 0) and is equivalent to the y-intercept of the graph. Growth Fraction (GF) is the proliferating proportion of the total RMS population and it is equivalent to the maximum LI plotted in the graph where all proliferating cells in the RMS are assumed to be labeled by BrdU at least once(GF= LIt; t≥ Tc-Ts). Ts and Tc are subsequently calculated using a non-linear least squares fit to the labeling index curve (Nowakowski et al., 1989).

3-Dimensional reconstruction of the RMS and its total cell population

Three mice from each genotype used in the cell cycle analysis were also used for a full reconstruction and quantitative analysis of the RMS to obtain the total volume and total number of cells in the RMS of each genotype. We used NeuroLucida and Neuroexplorer software (version 4, 2000 by MicroBrightField, Inc.). Consecutive sections were cut at 8 µm thickness and stained with CV. The initial appearance of the RMS marked the beginning of the analysis. The cell density of the total RMS of each half brain was calculated from every 5th section. The cell densities were then summed and divided by total sections that were measured to arrive at the mean density. Total cell number was calculated for the entire RMS using the density and volume measurements. The total cell number was a rough estimate because these counts are inflated due to the inclusion of double cell counts from cells that extended across multiple sections.

Quantitative Trait Locus (QTL) Analysis

QTL mapping was performed using WebQTL, a module of the GeneNetwork (www.genetwork.org) which is an open-access online database that contains detail genotype information of the RI strains generated from 8514 informative markers. WebQTL implements both simple and composite interval mapping methods described by Knott et al. (2002), and also scans the genome for non-linear, epistatic interactions among two or more loci. Likelihood ratio statistic (LRS) was computed to assess genotype-phenotype association and determine QTL. Genome-wide significance levels for assessing the confidence of the linkage statistics were estimated by comparing the peak LRS of correctly ordered data sets with LRSs computed for 1,000 permutations (Churchill & Doerge, 1994). Permutation tests are a widely accepted method for determining the probability of the association occurring by chance. The LRS score can be converted to likelihood of the odds (LOD) score by dividing by 4.61, and we used the conventional 2.0 LOD drop-off interval to define the confidence limits of QTL peaks as recommended by Manichaikul and colleagues (2006). AXBXA RI genotypes and marker distribution patterns are downloadable at http://www.genenetwork.org/dbdoc/AXBXAGeno.html. Phenotypic data on the BrdU-labeled cells in the RMS and SGZ for the AXB/BXA lines have been deposited in GeneNetwork (Trait ID # 10124 and 10125).

Candidate gene analysis

We used three complementary approaches to identify candidate genes in the QTL region that modulate the number of proliferative cells in the RMS: 1) genes were assessed as to their involvement in neurogenesis, cell proliferation and cell cycle using the ontological information provided by Entrez Gene (NCBI; www.ncbi.nlm.nih.gov) and Mouse Genome Informatics (MGI; http://www.informatics.jax.org), 2) the Allen Brain Atlas (ABA; www.brainatlas.org) was used to examine the expression pattern of each gene in the adult mouse brain, 3) we also investigated whether our list of genes were involved in any signaling pathways that were known to regulate adult neurogenesis. We carried out our assessment by first creating a list of 30 targeted genes that were key components of known pathways described in supplementary material, Table S1. We then submitted both the targeted genes and the QTL genes to the Database for Annotation, Visualization and Integrated Discovery (DAVID; http://david.abcc.ncifcrf.gov/summary.jsp), and the functional annotation and clustering tools at DAVID helped us determine whether the QTL genes share any pathways and/or Gene Ontology (GO) terms with the targeted genes. In general, we considered a strong candidate to be associated with GO terms like cell proliferation, expressed in the adult mouse brain, and involved in known pathway(s) that regulated adult neurogenesis.

Statistical analysis

Statistical analyses were performed with JMP v8.0 statistical software (SAS Institute, Cary, NC). For all analysis of BrdU+ cells count and analysis on cell cycle, data were expressed as mean values ±SEM and were considered significant at p < 0.05. Two-tailed Student's t tests were used when comparing the two parental strains. The linear density of BrdU+ cells of different RI strains were compared by one-way analysis of variance (ANOVA). Normality of data distribution was examined using Shapiro-Wilk W Test.

Both age and sex were previously identified as regulatory factors influencing adult neurogenesis (Enwere et al. 2004; Tanapat et al. 1999), so we wanted to examine whether the number of proliferative cells travelling along the RMS was influenced by these two variables. Age effect on phenotype was examined by regression analysis and gender effect was assessed by fitting one-way ANOVA as a linear model. We also examined the effects of body weight using linear regression.

Since all three variables may serve as potential confounding covariates that influence our genetic linkage analysis, we adjusted the RMS linear density for age, body weight, and also sex. Residuals were obtained from a multiple regression fitting all three covariates for linear density (Rosen et al., 2009). The adjusted RMS linear density was then calculated from adding the residuals to the average RMS linear density by strain (Lu et al. 2008). Both the residuals and the adjusted linear density are normally distributed and are not significantly associated with any of the three regressors. The adjusted RMS linear density data is available at the GeneNetwork (Trait ID # 10167) and it is positively correlated with the original trait data (r= 0.97; p < 0.0001).

Results

Differential BrdU labeled cells in the RMS between A/J and C57BL/6J

The adult RMS is composed largely of neuroblasts that give rise to different subtypes of interneurons in the OB (Lledo et al., 2008). In order to quantify strain differences in the actively dividing population of neuroblasts, we used BrdU, a thymidine analog which gets incorporated into DNA during the S-phase of the cell cycle and is commonly used in the detection of proliferating cells. After 1 hour of BrdU exposure, the RMS of A/J mice had a significantly larger population of labeled S-phase (i.e., BrdU- immunoreactive) cells/mm (81 ± 4.56 SEM, n = 6) than C57BL/6J mice (49 ± 4.85 SEM, n = 9) (p= .0006; Fig. 2). Differences in BrdU-labeled cells could be due to either A/J having more rapidly proliferating cells than C57BL/6J, or it could be that the proliferating cells in A/J have a relatively longer S-phase to overall cell cycle length compared to C57BL/6J. We distinguished between these two possibilities by determining the total numbers of cells in the RMS, estimating the proportion of actively dividing cells, and measuring their cell cycle and S-phase lengths.

FIG. 2.

FIG. 2

Open in a new tab

The mean linear density of proliferating cells ± SEM in the RMS of 27 AXB/BXA RI strains (white bars) and their parental strains, C57BL/6J (black bar), and A/J (gray bar). The sample size per strain is indicated in the bars.

Shape, orientation, and size of the RMS in A/J and C57BL/6J

The RMS from the C57BL/6J and A/J mice was reconstructed from serial sagittal sections to compare their three-dimensional course and to determine the total numbers of RMS cells in each strain. Our immunohistological staining analysis and imaging revealed that the general configuration of the RMS in both strains was similar (Fig. 3). Moreover, A/J had ~40% more cells in the RMS than C57BL/6J (A/J = 52659 ± 535 SEM and C57BL/6J = 37130 ± 731 SEM) (Fig. 3B&C).

FIG 3.

FIG 3

Open in a new tab

(A) Schematic 3D illustration of the RMS (orange) relative to other brain structures including the ventricular system (V), hippocampus (Hipp), and the olfactory bulb (OB). Neural precursors generated in the subventricular zone which is adjacent to the lateral ventricular wall (blue) migrate tangentially to the OB through the RMS. Once these cells reach the OB, they break-off and travel radially before differentiating into interneurons. Shapes of Hipp, V, and OB are adapted and modified, with permission, from the wild-type 3D mouse brain published by Bock et al. (2006). Top-forward views of the 3D RMS structure in the A/J (B) and C57BL/6J (C) brains were reconstructed from serial sagittal sections. Brackets in (B)(C) indicate the total number of RMS cells ± SEM for each strain (n= 3 per group).

Cell cycle analysis confirmed that A/J had higher RMS proliferative capacity than C57BL/6J

At the cellular level, we wanted to determine if the differences in BrdU labeled cells between A/J and C57BL/6J are due to differences in cell cycle parameters as explored in the dentate gyrus by Hayes & Nowakowski (2002). First, we determined the labeling index (LI) at each time point under study for both parental strains (Fig. 4). There was an initial increase of LI with lengthening BrdU exposure time, indicative of a constantly dividing cell population. For both strains, the LI reached a plateau of ~0.2, suggesting that the actively dividing populations in the RMS accounts for approximately 20% of the total RMS cell population. Using the total RMS cell numbers described in Fig. 3 and a growth fraction (GF) value (i.e., the proportion of proliferating cells to the total number of cells in the population) of 0.2, we estimated that the total numbers of actively dividing cells in the RMS were 10531 ± 107 SEM and 7426 ± 146 SEM for A/J and C57BL/6J, respectively. Moreover, the quantitative analysis of the LI curves showed that there are no significant differences in the cell cycle parameters of the two RMS populations. The ratio of Ts/Tc was similar (~0.57), indicating that the relative length of the S-phase (Ts) to the whole cell cycle (Tc) was the same for the two strains. The length of the cell cycle for the proliferative populations in the RMS ranged from 10.5 h (A/J) to14.5 h (C57BL/6J), and these values overlap with the cell cycle length for the proliferative population in the dentate gyrus (12–14 h) and are also within the 8–18 h range of cell cycle lengths detected in progenitor cells lining the ventricular cavity of the developing cerebral neocortex (Hayes & Nowakowski, 2002; Takahashi et al., 1995). Although the lengths of cell cycle and S-phase for the proliferative population in A/J RMS appeared to be shorter than the lengths detected in the C57BL/6J RMS, such differences did not reach statistical significance. Therefore, the differences in the number of BrdU-labeled cells in the RMS of two strains reflected differences in the actual number of proliferative cells and was not due to differences in cell cycle or S-phase lengths. In line with this conclusion, the proliferative population size in the A/J RMS was ~40% larger than C57BL/6J RMS.

FIG. 4.

FIG. 4

Open in a new tab

Cell cycle analysis in the RMS of adult A/J (A) and C57BL/6J mice (B). Graphs of labeling indices from the counts of BrdU-labeled and non-BrdU-labeled cells after a series of BrdU injections into adult A/J and C57BL/6 mice. The squares represent the average labeling index (LI) ± SEM (on Y-axis), for each time point (on X-axis).The line extending from each square is the least squares fit. The growth fraction (GF), Length of the cell cycle (Tc in hours), and the length of the S-phase (Ts in hours) for each genotype were estimated from the equations provided in the graphs. Differences in the cell cycle parameters are observed between the two strains with the A/J RMS cells having shorter Ts and Tc than C57BL/6J RMS. Although suggestive, these differences are not statistically significant.

Proliferation in the RMS was highly variable among the AXB/BXA RI strains

The numbers of BrdU+ proliferating cells in the RMS of the two inbred strains indicate that these two strains have an inherent difference in proliferative capability in the adult RMS. To determine the genetic bases for this difference, we used the 27 BXA/AXB RI strains generated from parental A/J and C57BL/6J mice. As an assay, we used the numbers of BrdU+ cells as determined from a single injection of BrdU given one hour prior to sacrifice. From this quantitative analysis, a substantial range of BrdU+ cells was detected in the RMS among RI strains (Fig. 2; Fig. 5). Strain averages were normally distributed and the linear density (BrdU+/mm) ranged from a high of 119.07 ± 15.95 in BXA25 to a low of 32.62 ± 4.19 in BXA7, with an average across all 27 strains of 78.11 ± 3.74 (Fig. 2). There is a three-fold difference between the minimum and the maximum linear density measured from the RI strains and this range extends beyond the differences observed between the parental strains. Heritability (h2) of proliferation in the adult RMS was determined by the ratio of inter-strain variance over the total variance which includes both inter- and intra- strain variance (Kempermann et al. 2006). The h2 is ~0.53 (F28, 117 =3.52; P < 0.0001), indicating that half of the variation in proliferation is accounted for by allelic variation.

FIG 5.

FIG 5

Open in a new tab

Representative sagittal sections of BrdU-labeled RMS in four separate lines of AXB/BXA RI adult mice given a single pulse of BrdU for one hour. These photomicrographs document the varying phenotypes seen in this set of recombinant inbred mice with some lines having abundant proliferating BrdU positive cells in RMS (A), some lines have little BrdU positive cells in RMS (B) while others have intermediate numbers of BrdU positive cells (C & D). Arrows indicate the start and end point of RMS. LV: Lateral ventricles; scale bar: 200 µm.

We performed statistical analyses to examine whether sex, age, and body weight are confounding factors that influence RMS proliferation. From our analysis, sex appeared to have no significant effect on RMS linear density (F1, 117= 0.56, p= 0.4544; females = 76.15 ± 2.57; males = 72.70 ± 3.81). Whereas, simple linear regression analysis showed that the linear density is negatively correlated with age (r = −0.47; p < 0.0001) and body weight (r= −0.37; p < 0.0001).

Identification of a significant QTL on Chr 11(RMS11a) for RMS proliferation

The AXB/BXA RI strains consist of unique combinations of haplotypes inherited from the parental strains which make these RI strains useful for mapping complex/quantitative trait and uncovering chromosomal regions that are responsible for the phenotypic differences observed in A/J and C57BL/6J. Using the online tool WebQTL (http://www.genenetwork.org/), we mapped linear density in the RMS (Fig. 2) and detected a highly significant QTL on the distal end of Chr 11 (Fig. 6). This significant QTL has a 1.5Mb wide peak that is centered at116.75 Mb on Chr 11 as defined by the 2.0- LOD support confidence interval (Lander & Botstein, 1989; Manichaikul et al., 2006). This locus is the first significant QTL to be described for proliferation in adult neurogenic regions of the mammalian brain and we name this locus RMS11a. From marker regression analysis, markers D11Mit103 and gnf11.125.992 located in RMS11a are significantly associated with trait variation (genome-wide P <0.05, LRS= 20.2, LOD= 4.38; Fig. 6D). The Genotypes at these markers revealed that having a C57BL/6J (B) allele in RMS11a is associated with a ~15 BrdU+ cells/mm increase in linear density compare to having an A/J (A) allele (F1, 24= 28.7, p < 0.0001). This finding is contrary to our expectation of having the A allele associated with high trait values and is addressed further in the Discussion.

FIG. 6.

FIG. 6

Open in a new tab

QTL mapping for variation in the proliferative cells traveling along the RMS generated by the WebQTL at the Gene Network. Whole genome interval mapping for QTL modulating the unadjusted RMS linear density (A) and for the adjusted RMS linear density (B) for age, sex, and body weight. X axis at the top panel represents the chromosomes (1–19, & X) and the blue y axis on the left depicts the likelihood ratio statistic (LRS). The gray and red horizontal lines across the LRS plot mark the genome-wide suggestive (p< 0.63) and significant (p< 0.05) thresholds, respectively. The highest LRS peak is located at the distal end of Chr 11. We named this QTL RMS11a. (C) LRS plot for the entire chromosome 11. The green and red segments represent the average additive effects of A/J “A” alleles and C57BL/6J “B” alleles, respectively, at a genetic marker. RI strains with the B allele at the chromosome 11 QTL region had a higher trait value on average when compared to strains with an A allele, as indicated by the red line parallel to the blue LRS peak. The magnitude of the additive effect is shown by the green colored Y axis on the right. (D–E) Screen captures of marker regression reports from mapping the unadjusted (D) and adjusted (E) RMS linear density. Two Chr 11 genetic markers, D11Mit103 and gnf11.125.992 are consistently associated with the highest LRS score. Here, the negative additive effect indicates that the trait value is increased by the B allele at RMS11a.

Since age and body weight are identified as covariates and sex has previously been found to influence hippocampal neurogenesis (Tanapat et al. 1999), we regressed the RMS linear density for each animal against these three variables and calculated the average residuals per strains. QTL mapping of variation in the adjusted RMS linear densities generated a whole genome scan LRS plot that resembled the plot produced from mapping with the unadjusted trait data (Fig.6B). A prominent QTL is mapped to the distal end of chromosome 11(RMS11a) and the genetic markers, D11Mit103 and gnf11.125.992, are again associated with the highest LRS score (Fig.6E). The B allele in this QTL interval increases trait value by ~24 BrdU+ cells/mm, suggesting the removal of covariates could unmask an even greater genetic effect on phenotype. With the mapping of average residuals, the strength of linkage at RMS11a decreased ~16. In additional to RMS11a, a new suggestive QTL is seen at the proximal end of Chr 2 at 25± 5Mb (genome-wide P< 0.63; LRS= 10.56; LOD= 4.61; Fig. 6B). Strains having a B allele in this Chr 2 QTL interval is associated with a ~22 BrdU+ cells / mm increase in linear density compared to strains carrying the A allele (Fig. 6E). To further explore the robustness of RMS11a and determine whether the mapping of this locus is confounded by differences in age, we mapped RMS linear density from animals that were 60 to 100 days old (n=98). Mapping with a narrowed age parameter located the same Chr 11 QTL on the distal end at 116.75 ± 0.75 Mb (see Supplementary material, Fig. S3; Trait ID: 10157). We also mapped RMS linear density using only adult female mice (n=83) and revealed a significant QTL mapped to the same Chr 11 region (see Supplementary material, Fig. S3; Trait ID: 10155). These results provide additional evidence that age and sex do not influence the identification of RMS11a.

A different QTL on Chr 3 was associated with variation in SGZ proliferation

The subgranular zone (SGZ) of the dentate gyrus (DG) is another well studied proliferative zone in the adult mammalian brain that contains a mixture of progenitors with limited self-renewal capacity (Seaberg and Van der Kooy 2002). We also examined the genetic architecture underlying the proliferative potential of these SGZ cells in comparison to the RMS. The average total number of BrdU+ cells was calculated in the SGZ of 27 AXB/BXA RI strains as described in the Methods section.

After exposing to BrdU for an hour, the C57BL/6J SGZ had higher numbers of BrdU immunoreactive cells (52 ± 2 SEM) than that of A/J (29 ± 2.5 SEM) (Fig. 7A). This reversal in phenotypic direction was intriguing and suggested different alleles are regulating the proliferative potential of RMS and SGZ cell populations. Similar to a previous study that quantified adult neurogenesis in 52 recombinant RI strains (29 BXD and 23 AXB/BXA strains), we also detected large inter-strain differences in SGZ cellular proliferation (Kempermann et al., 2006). However, none of the RI strains had more cells than C57BL/6J, but more than half of the RI strains had fewer cells than in A/J (Fig. 7A). Genetic analysis using QTL interval mapping of the SGZ phenotype showed that one suggestive QTL modulated the number of proliferating SGZ cells was located on Chr 3 at 102 ± 7 Mb (genome-wide P< 0.63; LRS= 12.79; LOD= 2.77) (Fig. 7B & C). We also found that having an A allele in the QTL 3 interval was associated with a 5 BrdU+ cells/mm increase in SGZ cellular proliferation when compared to RI strains with the B allele (Fig. 7C). This SGZ QTL does not correspond with those seen for the RMS suggesting that the RMS and SGZ have region-specific molecular mechanisms for controlling adult neurogenesis.

FIG. 7.

FIG. 7

Open in a new tab

QTL mapping for variation in the BrdU labeled cells in the SGZ of hippocampus. (A) The total number of proliferating cells ± SEM counted in the SGZ of 27 AXB/BXA RI strains (white bars) and their parental strains, C57BL/6J (black bar), and A/J (gray bar). The sample size per strain is indicated in the bars. (B) Genome scan LRS plot has identified a suggestive QTL located on Chr 3. (C) Interval mapping of the entire Chr 3 further revealed the location of suggestive QTL at 102 ± 7 Mb. The green and red segments represent the average additive effects of A/J “A” alleles and C57BL/6J “B” alleles, respectively, at a genetic marker. RI strains with the A allele at the chromosome 3 QTL region had a higher trait value on average when compared to strains with the B allele, as indicated by the green line parallel to the blue LRS peak. The magnitude of the additive effect is shown by the green colored Y axis on the right.

Candidate genes residing in RMS11a

In this study, we identified a robust QTL associated with variation in RMS cellular proliferation on mouse chromosome 11, which is syntenic with human chromosome 17q25.1. We named this novel QTL RMS11a and there are two prominent features of this QTL: (1) it is centered at 116.75Mb of chromosome 11, and (2) it is 1.5Mb wide as defined by the 2.0- LOD support confidence interval. A total of 36 genes, 25 known and 11 predicted, reside in this QTL interval (Table 1).

TABLE 1.

A list of 36 genes residing in the Chr11 QTL (RMS11a) 2.0 LOD supported 95% confidence interval. The SNP count indicates the number of SNPs that differs between the two parental strains, A/J and C57BL/6J.

Gene Symbol Gene Name Position on
Chr11 (Mb)		 Gene
Length (Kb)		 SNP
Count		 Gene Ontology (GO) Annotations
Fbf1 Fas(TNFRSF6) binding factor 1 116.003598 25.894 13 protein binding, cytoplasm
2310004N24Rik RIKEN cDNA2310004N24 gene 116.031038 16.464 0 --
Acox1 acyl-Coenzyme A oxidase1, palmitoyl 116.033201 27.158 56 acyl-CoA dehydrogenase activity, fatty acid beta-oxidation, spermatogenesis
Cdk3 cyclin-dependent kinase3 116.036087 4.285 8 cyclin-dependent protein kinase activity, cell cycle, cell division, mitosis
Evpl envoplakin 116.081872 17.533 31 cell junction, cytoplasm, cytoskeleton, keratinization
Srp68 signal recognition particle 68 116.106479 29.052 47 ribonucleoprotein complex, endoplasmic reticulum targeting
Galr2 galaninreceptor 2 116.142252 3 6 G-protein coupled receptor protein signaling pathway, neuron development
Exoc7 exocystcomplex component 7 116.150496 17.491 19 cytoplasm, plasma membrane, exocytosis, protein transport
Rnf157 ring finger protein 157 116.168987 76.680 0 metal ion binding, protein binding, zinc ion binding
Foxj1 forkhead box J1 116.192019 4.649 8 actin cytoskeleton organization, negative regulation of T cell proliferation
Prpsap1 phosphoribosylpyrophosphate synthetase-associated protein 1 116.287418 23.358 0 nucleotide biosynthetic process, ribose phosphate diphosphokinase activity
1110014K08Rik RIKEN cDNA 1110014K08 gene 116.295407 4.983 18 --
Qrich2 glutamine rich 2 116.302638 13.023 18 --
Sphk1 sphingosinekinase1 116.39466 5.750 3 Positive regulation of cell proliferation, blood vessel and brain development
Ube2o ubiquitin-conjugating enzyme E2O 116.399066 43.695 87 ubiquitin-protein ligase activity, post-translational protein modification
1700074G04Rik RIKEN cDNA1700074G04 gene 116.450949 0.147 3 --
Aanat arylalkylamineN-acetyltransferase 116.455 3.858 19 acyltransferaseactivity, melatonin biosynthetic process
Rhbdf2 rhomboid 5 homolog 2 (Drosophila) 116.459482 28.851 42 endoplasmic reticulum, integral to membrane
Cygb cytoglobin 116.506908 8.719 24 oxygen transporter activity, neuron projection, oxygen transport
1810032O08Rik RIKEN cDNA 1810032O08 gene 116.532973 4.137 12 --
St6galnac2 ST6-N-acetylgalactosaminide alpha-2,6-sialyltransferase 2 116.538018 17.956 38 sialyltransferaseactivity, protein amino acid glycosylation
BC018473 cDNAsequence BC018473 116.571499 7.207 0 --
St6galnac1 ST6-N-acetylgalactosaminide alpha-2,6-sialyltransferase 1 116.626338 10.483 27 sialyltransferaseactivity, protein amino acid glycosylation
Mxra7 matrix-remodelling associated 7 116.664717 24.643 63 integral to membrane
Jmjd6 jumonji domain containing 6 116.698745 6.018 9 oxidoreductaseactivity, apoptosis, blood vessel development, cell differentiation
1110005A03Rik RIKEN cDNA 1110005A03 gene 116.704828 6.225 0 integral to membrane
Sfrs2 splicing factor, arginine/serine-rich 2 (SC-35) 116.71121 3.198 0 nuclear speck, nucleus, spliceosomalcomplex, mRNA processing, RNA splicing
Mfsd11 major facilitator superfamily domain containing 11 116.715328 21.623 13 integral to membrane
Mgat5b mannoside acetylglucosaminyltransferase 5, isoenzyme B 116.780176 68.082 161 alpha-1,6-mannosyl-glycoprotein 6-beta-N-acetylglucosaminyltransferase activity
2810008D09Rik RIKEN cDNA 2810008D09 gene 116.893189 2.166 0 --
Sec14l1 SEC14-like 1 (S. cerevisiae) 116.976562 43.973 81 --
Sept9 septin 9 117.01575 162.665 127 GTP binding, nucleotide binding, cell cycle, cell division
A930024O17Rik RIKEN cDNA A930024O17 gene 117.245886 0.807 0 --
OTTMUSG00000003 Gm11733 predicted gene 11733 117.345681 4.647 0 --
2900041M22Rik RIKEN cDNA 2900041M22 gene 117.472689 1.422 1 --
Tnrc6c trinucleotiderepeat containing 6C 117.515602 109.151 136 gene silencing by RNA, regulation of translation
Open in a new tab

Of all the genes we examined, two genes met all our three candidate gene criteria (see Materials and Methods) and are considered as priority genes for future analysis. One of them is sphingosine kinase 1 (Sphk1) that is expressed in adult murine brain and has been implicated in cellular processes including cell proliferation and cell survival (Kohama et al., 1998; Hait et al., 2006). One major role of Sphk1 is to generate Sphingosine-1-phosphate (S1P) from its metabolic precursor sphingosine, and S1P is a lipid second messenger that plays an important role in both vasculogenesis and neurogenesis (Harada et al., 2004; Mizugishi et al., 2005). Our pathway analysis using DAVID (http://david.abcc.ncifcrf.gov:8080/) showed Sphk1 is part of the Vascular Endothelial Growth Factor (VEGF) Signaling pathway that when activated increases proliferation in the SVZ and also modulates migration of the neural progenitors in the RMS (Wittko et al., 2009). There are three SNPs identified when comparing the A/J and C57BL/6J genome at the Gene Network’s variant browser. One is a synonymous SNP located in exon 5, while the remaining two SNPs-one located in intron 2 and the other in intron 5- have unknown functions.

Another gene, the galanin receptor 2 (Galr2) also emerged as a strong candidate gene that may control the number of proliferating cells in the RMS. Galr2 is the receptor for galanin, a neuropeptide involved in mood regulation is expressed throughout the brain including SVZ, RMS, and DG (Ma et al., 2008). Activation of Galr2 through the binding of galanin has been linked to increased hippocampal neurogenesis in the seizure-induced injured brain (Mazarati et al., 2004). Moreover, the activation of Galr2 induces the mitogen-activated protein kinase (MAPK) pathway (Wang et al., 1998). MAPK is a complex signal transduction pathway that promotes cell division and can also be mediated through the binding of extracellular growth factors (e.g. FGF-2 and EGF) to cell surface receptors (Fgfr2 and Egfr). Both FGF2 and EGF have been previously implicated to regulate adult neurogenesis in vivo (Frinchi et al., 2008; Mudò et al., 2009; Doetsch et al., 2002; Basak & Taylor, 2009). Disregulation of Galr2 has been linked to depression in human and mouse (Lu et al., 2007). There are currently six unknown SNPs that exist between A/J and C57BL/6J. Two are in 5’ UTR, three are in intron-1, and one is in 3’UTR.

Septin 9 (Sept9) and cyclin-dependent kinase 3 (cdk3) and are two other genes that are worth mentioning because even though they are not directly linked to neurogenesis, they are both cell cycle regulatory genes. Sept9 is involved in the progression through G1 of the cell cycle and it is highly expressed throughout the adult mouse brain (Gonzalez et al., 2009). Whereas, cdk3 is expressed at low levels throughout the adult mouse brain and it is required for G1-S transition (Braun et al., 1998). The Sept9 gene is the largest gene (~162 Kb) identified in the QTL interval and it harbors 127 SNPs with unknown functions. By contrast, the cdk3 gene is shorter in length (~4.3kb) and contains only 8 unknown SNPs.

Discussion

The RMS is a major source of new neurons in the adult brain. Despite the intensive analysis of the cytoarchitecture of the RMS, the molecular genetic mechanisms regulating the size and behavior of the RMS proliferating population remain elusive. In this study, we investigated the genetic contribution of the natural variation observed in RMS proliferation. By using BrdU immunohistrochemistry and stereological methods, we have demonstrated that the numbers of proliferating cells in the RMS is highly variable among C57BL/6J, A/J and their RI strains, and based on QTL mapping, this phenotypic variation is generated in part by the allelic differences at a locus on Chr 11.

In this study, we discovered that the proliferative capacity of the adult RMS behaves as a quantitative trait where the numbers of rapidly proliferating cells in the RMS varies 1.7 fold between the parental strains (C57BL/6J and A/J) and 3.6 fold among the AXB/BXA RI strains. We found that these differences are not due to the strain differences in S-phase lengths based upon our analysis of the cell cycle. This is the first characterization of the proliferative behavior of dividing precursors in the mouse RMS in terms of cell cycle kinetics. Our cell cycle analysis did not detect any significant differences in either cell cycle or S-phase lengths between A/J and C57BL/6J, suggesting that it is the differences in the number of proliferating RMS cells that account for the strain differences.

To our knowledge, only one other report has examined strain differences in RMS proliferation. In that report, Lee et al. (2003) found no differences between C57BL/6J and two other inbred strains namely, 129/S1 and BALB/c mice at 8 weeks of age. However, using the counting parameters we have established in this study, we found differences between these three strains at 2 months of age with 129/S1 producing the highest number of RMS proliferating cells, followed by BALB/c, and then C57BL/6J (unpublished data). The discordant results are likely due to the region that was quantitated. In the Lee et al. study, the authors quantified the total numbers of BrdU-positive neuroblasts in four zones along the SVZ-RMS axis and one of the zones included the anterior SVZ caudal to the tip of the lateral ventricle, which was excluded from our work. We purposely left out the SVZ in this study because the cellular composition of the SVZ is far more complex than that of the RMS (Alvarez-Bullya & Garcia-Verdugo, 2002; Merkle et al, 2007). For example, some of the cell types that are present in the SVZ, but absent in the RMS include oligodentrocyte progenitors and transit amplifying precursors that are also actively dividing like the neuroblasts (Doetsh et al., 1997); thus making the comparison between SVZ and RMS counts tenuous. Interestingly, a re-examination of just the RMS in Lee et al. study showed inter-strain variation in the total numbers of BrdU-positive neuroblasts that were very much in line with the strain differences observed in our unpublished study.

The wide range of natural variation in the RMS proliferative capacity in the AXB/BXA RI lines made it possible for us to explore the genetic underpinning of cell proliferation in the adult RMS using QTL analysis. The strain distribution pattern was suggestive of the inheritance of the trait through a major gene locus on distal Chr 11 and the mapping of this 1.5 Mb wide QTL was not confounded by age, sex, and body weight. The identification of a narrow QTL is usually achieved by phenotyping a large genetic reference panel of RI strains, yet we were able to achieve this level of precision by “subphenotyping” the regions involved in olfactory bulb neurogenesis and by refining our quantitative analysis to only the RMS.

Basic Mendelian inheritance patterns would suggest that RI strains with more BrdU-positive cells would inherit cell proliferation alleles from the A/J parent, while strains with fewer BrdU-positive cells would inherit fewer cell proliferation alleles from the C57BL/6J genome. A close examination of the allelic alignments of the genetic markers located in the RMS11a QTL interval shows an unexpected pattern. A single B allele in this interval had an additive effect on the proliferation of the RMS which was opposite to our phenotype observation that A/J had more proliferating cells in the RMS. QTLs showing the unexpected allelic contribution as observed here are known as “cryptic QTLs”. These QTLs usually result from the epistatic interaction of genes (Weller et al., 1998; Lauter & Doebley, 2002). Mapping of the adjusted proliferative linear density have revealed a suggestive QTL on Chr 2 and also increased the LRS score of two other loci, one on Chr 4 and the other one on Chr 6, near to the suggestive level. These findings suggest other loci are likely involved in modulating the number of RMS proliferating cells. A pair scan for two-locus epistatic interactions was performed by WebQTL and showed no significant interactions between the markers in RMS11a and loci on other chromosomes. To better assess interactions among genetic loci, a larger sample size is usually required to improve statistical power and sensitivity of the pair scan. We are currently replicating this study using another reference population of mice- a set of BXD RI strains (70 strains)-in hopes of validating the QTLs we have identified, discovering additional QTL(s), and detecting significant genetic interaction(s).

We also examined the rapidly proliferating population in the adult SGZ to determine if similar regions of the genome were implicated and hence, a common genetic foundation underlying adult neurogenesis in the mouse. We were surprised on three accounts: 1) we found opposite values for BrdU-labeling in SGZ compared to the RMS; that is the C57BL/6J SGZ had more BrdU immunoreactive cells than that of A/J SGZ, 2) our QTL analysis of the SGZ data showed no overlap with the mapped QTLs in the RMS, and 3) the SGZ QTL we located on Chr 3 is different from the proximal Chr 5 QTL identified by Kempermann et al. (2006) analysis of proliferation, as determined by the number of Ki-67 immuno-positive cells in the SGZ of 29 BXD RI lines. Findings from 1) and 2) suggest that the numbers of rapidly dividing cells in the SGZ are differentially regulated by a separate set of genetic variants and their underlying networks. Evidence of the intrinsic differences between the SGZ and SVZ progenitors contributing to the differential proliferative capacity of these cells is provided by Seaberg & van der Kooy’s 2002 study where they cultured progenitors isolated from DG and SVZ. Unlike the SVZ cells, DG cells lacked multipotentiality and had limited self-renewal in vitro (Seaberg & van der Kooy 2002). The cellular composition and microenvironment of SGZ and SVZ are also different, and there is evidence for regional-specific regulation on the proliferative potential of adult NSCs and their progeny. For example, ependymal cells lining the ventricles and adjacent to the SVZ B cells (precursors with astrocytic morphology) are found to be local providers of factors like noggin and pigment epithelium-derived factor (PEDF) that may be required for maintaining the stemness of the B cells (Ramirez-Castillejo et al., 2006; Lim et al., 2000). These ependymal cells are not present in the SGZ niche and their absence may explain the lack of stem-like qualities of the SGZ progenitors (Seaberg & van der Kooy 2002; Bull & Bartlet, 2005). At present, only one other study used the recombinant inbred strains to dissect the genetic architecture of adult neurogenesis (Kempermann et al., 2006). This study mapped the variation in SGZ proliferation in a BXD reference panel (derived from C57BL/6J and DBA/2J) to a separate locus from the Chr 3 QTL we identified from mapping variation in the AXB/BXA panel. These differences likely point to the genetic complexities that underlie adult neurogenesis into which we are tapping by using the diverse genetic repertoires presented in the two RI lines.

Neurogenesis in the adult brain is a polygenic, multifactorial phenomenon that encompass several processes including proliferation, migration of precursors, and then the differentiation and survival of new born neurons. The net neurogenesis is reflected by the numbers of neurons that get functionally integrated into preexisting circuitry. Kempermann and colleagues (2006) detected inter-strain variation in not just the numbers of SGZ proliferating cells (Ki-67+), but also in the numbers of surviving (BrdU+) and differentiated neurons (BrdU+NeuN+) in the DG. QTL mapping of these three parameters of hippocampal neurogenesis showed little overlap in LRS peaks, suggesting that these three traits are modulated by different genetic loci. A similar analysis has not been done in the RMS. In this study, we investigated the differences in cell proliferation in the RMS of different mouse strains. It is currently unknown whether the observed inter-strain differences will persist into later stages of the OB neurogenesis. The continuous supply of new neurons from the RMS is positively correlated with the olfactory bulb weight which increases linearly overtime in the mouse brain (Williams et al., 2001). We correlated both the adjusted and unadjusted RMS proliferation data with the olfactory bulb weight (Trait ID: 10093) deposited at the AXB/BXA Published Phenotypes database of Gene Network, and no correlation between these two phenotypes was found. This suggests that having more proliferating cells in the RMS does not translate into a larger number of cells in the OB. Clearly, there are other factors regulating the survival and integration of newly generated neurons to the specific bulb layers, mainly the granule and the glomerular cell layers. It has been shown that an enriched olfactory experience and olfactory learning can increase the survival of newly born OB neurons in the adult (Rochefort et al., 2002; Alonso et al., 2006; Mandairon et al., 2006). Another study has examined the functional consequences of having differential numbers of neuroblasts traveling along the SVZ-RMS axis in three inbred strains: C57BL/6J, BALB/c, and 129/S1 (Lee et al., 2003). The authors of this study reported a casual association between neuroblasts behavior and olfactory function where C57BL/6J had the least numbers of RMS neuroblasts and the lowest olfactory sensitivity compared to the other two strains. However, this association was not sustained by the observations obtained from the other two strains, where BALB/c had the greatest olfactory sensitivity but did not have the highest number of neuroblasts. Interestingly, a prior assessment of olfactory discrimination learning in 13 adult (10–18 weeks old) inbred mouse strains by Brown and colleagues revealed that the C57BL/6J strain was capable of acquiring odor discrimination faster than most of the other strains including A/J (data available at the Mouse Phenome Database; MPD:22531, 22532, 22570). Taken together, proliferation in RMS does not appear to be a good predictor of net OB neurogenesis, OB structure, and function.

Here, we considered the RMS as a discrete neurogenic structure and our results demonstrated the variable and heritable nature of cell proliferation in the RMS. A major QTL called RMS11a is indentified on distal chromosome 11 for regulating the numbers of rapidly dividing precursors in the RMS but not in the SGZ. Furthermore, a subset of polymorphic genes underlying the RMS11a confidence interval have emerged as strong candidates due to their role in either cell cycle progression or involvement in signaling pathways known to regulate cell proliferation. Future analysis of these genes will include measuring the transcript and protein abundance in RMS cells and correlating their expression profiles with phenotypic data on the numbers of proliferating cells in the RMS, as well as determining the in vitro and in vivo functions of these genes in RMS proliferation. Overall, our study provides strong evidence for the allelic effects on neural proliferation and a solid framework for further exploration of other genetic loci and gene variants that are part of the complex regulation of adult neurogenesis. Genetic insights gained from these studies may contribute to the future development of neural stem cell therapies used to compensate for the loss of neurons in neurodegenerative diseases and brain injuries (Elder et al., 2006; Maysami et al., 2008).

Supplementary Material

Supp Fig s1. Fig. S1.

Comparison of two BrdU-labeled cell counting methods for quantifying proliferative cells in the RMS. (A) BrdU+ cell count from single best section containing a complete RMS extension from the lateral ventricle to the olfactory bulb significantly correlates with total BrdU+ cell count from 10 sections (80µm intervals) encompassing the entire medial to lateral extent of the RMS; P < 0.0001. (B) The linear density (BrdU+ cells/mm) calculated from a single best section also correlates with the total BrdU+ cell count determined from the 10 sections; P < 0.0001. Each data point represents counts obtained from a randomly selected recombinant inbred mouse.

Supp Fig s2. Fig. S2.

Schematical sagittal view of an adult mouse brain highlighting the four RMS representative segments (pink squares) selected for measuring the cell density and estimating the proliferative population in the RMS of A/J and C57BL/6J. All cells within these segments were counted and the corresponding areas were measured. The cell densities across all four regions were then averaged to give one value per animal. The general shape and trajectory of the RMS from the subventricular zone of the lateral ventricle (LV) to the olfactory bulb (OB) can be divided into three major components: vertical arm, the elbow, and the horizontal arm of the RMS.

Supp Fig s3. Fig. S3.

Age and sex did not influence the identification of RMS11a. (A) QTL Mapping for variation in the RMS linear density (BrdU+/mm) of RI strains ranging from 60-100 days old (n= 98; the original data contains animal ranged from 60-150 days). Genome scan LRS plot showed three suggestive QTL, one on Chr 11 (RMS11a), one on Chr 2, and another one on Chr 18. (B) QTL mapping for variation in the RMS linear density from adult female mice only (n= 83). Interval mapping also revealed a significant QTL mapped to RMS11a. (C) (D) are screenshots of the marker regression reports for mapping with narrowed age parameter and from mapping with female mice only. Trait value was consistently increased by theC57BL/6J allele represented by the negative additive effect value; whereas, the A/J allele is represented by positive additive effect value.

Supp Table s1. Table S1.

Signaling pathways and genes controlling the fate of adult neural stem cells and their progenitors. Information provided here was used for pathway analysis of QTL genes. Candidate genes were also assessed as to their interaction with genes known to regulate the cell cycle of adult neural progenitors.

Acknowledgements

This work was supported by a grant from the Methodist Chair in Neuroscience (DG), National Institute of AG18245 (DG), NIAAA U01AA014425 (LL), and P20 DA021131 (RW). We thank Derek Rains, Gurjit Rai, Meifen Lu, Richard Cushing, Erich Brauer, and Alan Weatherford for their invaluable technical assistance.

Abbreviations

BrdU

bromodeoxyuridine

CV

cresyl violet

GF

growth fraction

LOD

likelihood of the odds

LRS

likelihood ratio statistic

NSCs

neural stem cells

OB

olfactory bulb

DG

dentate gyrus

QTL

quantitative trait locus

RI

recombinant inbred

RMS

rostral migratory stream

SGZ

subgranular zone

SVZ

subventricular zone

Tc

the total cell cycle time

Ts

the S-phase time.

References

  1. Ahn S, Joyner AL. In vivo analysis of quiescent adult neural stem cells responding to Sonic hedgehog. Nature. 2005;437:894–897. doi: 10.1038/nature03994. [DOI] [PubMed] [Google Scholar]
  2. Alonso M, Viollet C, Gabellec MM, Meas-Yedid V, Olivo-Marin JC, Lledo PM. Olfactory discrimination learning increases the survival of adult-born neurons in the olfactory bulb. J. Neurosci. 2006;26:10508–10513. doi: 10.1523/JNEUROSCI.2633-06.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Alvarez-Buylla A, García-Verdugo JM, Tramontin AD. A unified hypothesis on the lineage of neural stem cells. Nat. Rev. Neurosci. 2001;4:287–293. doi: 10.1038/35067582. [DOI] [PubMed] [Google Scholar]
  4. Alvarez-Buylla A, Garcia-Verdugo JM. Neurogenesis in adult subventricular zone. J. Neurosci. 2002;22:629–634. doi: 10.1523/JNEUROSCI.22-03-00629.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Annenkov A. The Insulin-Like Growth Factor (IGF) Receptor Type 1 (IGF1R) as an Essential Component of the Signalling Network Regulating Neurogenesis. Mol. Neurobiol. 2009;40:195–215. doi: 10.1007/s12035-009-8081-0. [DOI] [PubMed] [Google Scholar]
  6. Bath KG, Mandairon N, Jing D, Rajagopal R, Kapoor R, Chen ZY, Khan T, Proenca CC, Kraemer R, Cleland TA, Hempstead BL, Chao MV, Lee FS. Variant brain-derived neurotrophic factor (Val66Met) alters adult olfactory bulb neurogenesis and spontaneous olfactory discrimination. J. Neurosci. 2008;28:2383–2393. doi: 10.1523/JNEUROSCI.4387-07.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Basak O, Taylor V. Stem cells of the adult mammalian brain and their niche. Cell. Mol. Life Sci. 2009;66:1057–1072. doi: 10.1007/s00018-008-8544-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bauer S, Patterson PH. Leukemia inhibitory factor promotes neural stem cell self-renewal in the adult brain. J. Neurosci. 2006;26:12089–12099. doi: 10.1523/JNEUROSCI.3047-06.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bock NA, Kovacevic N, Lipina TV, Roder JC, Ackerman SL, Henkelman RM. In vivo magnetic resonance imaging and semiautomated image analysis extend the brain phenotype for cdf/cdf mice. J. Neurosci. 2006;26:4455–4459. doi: 10.1523/JNEUROSCI.5438-05.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Braun K, Hölzl G, Soucek T, Geisen C, Möröy T, Hengstschläger M. Investigation of the cell cycle regulation of cdk3-associated kinase activity and the role of cdk3 in proliferation and transformation. Oncogene. 1998;17:2259–2269. doi: 10.1038/sj.onc.1202145. [DOI] [PubMed] [Google Scholar]
  11. Bull ND, Bartlett PF. The adult mouse hippocampal progenitor is neurogenic but not a stem cell. J. Neurosci. 2005;25:10815–10821. doi: 10.1523/JNEUROSCI.3249-05.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Carlén M, Meletis K, Göritz C, Darsalia V, Evergren E, Tanigaki K, Amendola M, Barnabé-Heider F, Yeung MS, Naldini L, Honjo T, Kokaia Z, Shupliakov O, Cassidy RM, Lindvall O, Frisén J. Forebrain ependymal cells are Notch-dependent and generate neuroblasts and astrocytes after stroke. Nat. Neurosci. 2009;12:259–267. doi: 10.1038/nn.2268. [DOI] [PubMed] [Google Scholar]
  13. Choi YS, Cho HY, Hoyt KR, Naegele JR, Obrietan K. IGF-1 receptor-mediated ERK/MAPK signaling couples status epilepticus to progenitor cell proliferation in the subgranular layer of the dentate gyrus. Glia. 2008;56:791–800. doi: 10.1002/glia.20653. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Churchill GA, Doerge RW. Empirical threshold values for quantitative trait mapping. Genetics. 1994;138:963–971. doi: 10.1093/genetics/138.3.963. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Colak D, Mori T, Brill MS, Pfeifer A, Falk S, Deng C, Monteiro R, Mummery C, Sommer L, Götz M. Adult neurogenesis requires Smad4-mediated bone morphogenic protein signaling in stem cells. J. Neurosci. 2008;28:434–446. doi: 10.1523/JNEUROSCI.4374-07.2008. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Doetsch F, García-Verdugo JM, Alvarez-Buylla A. Cellular composition and three-dimensional organization of the subventricular germinal zone in the adult mammalian brain. J. Neurosci. 1997;17:5046–5061. doi: 10.1523/JNEUROSCI.17-13-05046.1997. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Doetsch F, Verdugo JM, Caille I, Alvarez-Buylla A, Chao MV, Casaccia-Bonnefil P. Lack of the cell cycle inhibitor p27Kip1 results in selective increase of transit amplifying cells for adult neurogenesis. J. Neurosci. 2002;22:2255–2264. doi: 10.1523/JNEUROSCI.22-06-02255.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Doetsch F, Petreanu L, Caille I, Garcia-Verdugo JM, Alvarez-Buylla A. EGF converts transit-amplifying neurogenic precursors in the adult brain into multipotent stem cells. Neuron. 2002;36:1021–1034. doi: 10.1016/s0896-6273(02)01133-9. [DOI] [PubMed] [Google Scholar]
  19. Elder GA, De Gasperi R, Gama Sosa MA. Research update: neurogenesis in adult brain and neuropsychiatric disorders. Mt Sinai J. Med. 2006;73:931–940. [PubMed] [Google Scholar]
  20. Enwere E, Shingo T, Gregg C, Fujikawa H, Ohta S, Weiss S. Aging results in reduced epidermal growth factor receptor signaling, diminished olfactory neurogenesis, and deficits in fine olfactory discrimination. J. Neurosci. 2004;24:8354–8365. doi: 10.1523/JNEUROSCI.2751-04.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Frinchi M, Bonomo A, Trovato-Salinaro A, Condorelli DF, Fuxe K, Spampinato MG, Mudò G. Fibroblast growth factor-2 and its receptor expression in proliferating precursor cells of the subventricular zone in the adult rat brain. Neurosci. Lett. 2008;447:20–25. doi: 10.1016/j.neulet.2008.09.059. [DOI] [PubMed] [Google Scholar]
  22. Gheusi G, Cremer H, McLean H, Chazal G, Vincent J-D, Lledo P-M. Importance of newly generated neurons in the adult olfactory bulb for odor discrimination. Proc. Natl. Acad. Sci. U.S.A. 2000;97:1823–1828. doi: 10.1073/pnas.97.4.1823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Gonzalez ME, Makarova O, Peterson EA, Privette LM, Petty EM. Up-regulation of SEPT9_v1 stabilizes c-Jun-N-terminal kinase and contributes to its pro-proliferative activity in mammary epithelial cells. Cell Signal. 2009;21:477–487. doi: 10.1016/j.cellsig.2008.11.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Groszer M, Erickson R, Scripture-Adams DD, Lesche R, Trumpp A, Zack JA, Kornblum HI, Liu X, Wu H. Negative regulation of neural stem/progenitor cell proliferation by the Pten tumor suppressor gene in vivo. Science. 2001;294:2186–2189. doi: 10.1126/science.1065518. [DOI] [PubMed] [Google Scholar]
  25. Hait NC, Oskeritzian CA, Paugh SW, Milstien S, Spiegel S. Sphingosine kinases, sphingosine 1-phosphate, apoptosis and diseases. Biochim. Biophys. Acta. 2006;1758:2016–2026. doi: 10.1016/j.bbamem.2006.08.007. [DOI] [PubMed] [Google Scholar]
  26. Harada J, Foley M, Moskowitz MA, Waeber C. Sphingosine-1-phosphate induces proliferation and morphological changes of neural progenitor cells. J. Neurochem. 2004;88:1026–1039. doi: 10.1046/j.1471-4159.2003.02219.x. [DOI] [PubMed] [Google Scholar]
  27. Hayes NL, Nowakowski RS. Dynamics of cell proliferation in the adult dentate gyrus of two inbred strains of mice. Brain Res. Dev. Brain Res. 2002;134:77–85. doi: 10.1016/s0165-3806(01)00324-8. [DOI] [PubMed] [Google Scholar]
  28. Imayoshi I, Sakamoto M, Ohtsuka T, Takao K, Miyakawa T, Yamaguchi M, Mori K, Ikeda T, Itohara S, Kageyama R. Roles of continuous neurogenesis in the structural and functional integrity of the adult forebrain. Nat. Neurosci. 2008;11:1153–1161. doi: 10.1038/nn.2185. [DOI] [PubMed] [Google Scholar]
  29. Jackson EL, Garcia-Verdugo JM, Gil-Perotin S, Roy M, Quinones-Hinojosa A, VandenBerg S, Alvarez-Buylla A. PDGFR alpha-positive B cells are neural stem cells in the adult SVZ that form glioma-like growths in response to increased PDGF signaling. Neuron. 2006;51:187–199. doi: 10.1016/j.neuron.2006.06.012. [DOI] [PubMed] [Google Scholar]
  30. Johnson MA, Ables JL, Eisch AJ. Cell-intrinsic signals that regulate adult neurogenesis in vivo: insights from inducible approaches. BMB Rep. 2009;42:245–259. doi: 10.5483/bmbrep.2009.42.5.245. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Kempermann G, Gage FH. Genetic influence on phenotypic differentiation in adult hippocampal neurogenesis. Brain Res. Dev. Brain Res. 2002;134:1–12. doi: 10.1016/s0165-3806(01)00224-3. [DOI] [PubMed] [Google Scholar]
  32. Kempermann G, Gast D, Kronenberg G, Yamaguchi M, Gage FH. Early determination and long-term persistence of adult-generated new neurons in the hippocampus of mice. Development. 2003;130:391–399. doi: 10.1242/dev.00203. [DOI] [PubMed] [Google Scholar]
  33. Kempermann G, Chesler EJ, Lu L, Williams RW, Gage FH. Natural variation and genetic covariance in adult hippocampal neurogenesis. Proc. Natl. Acad. Sci. U.S.A. 2006;103:780–785. doi: 10.1073/pnas.0510291103. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Kim EJ, Leung CT, Reed RR, Johnson JE. In vivo analysis of Ascl1 defined progenitors reveals distinct developmental dynamics during adult neurogenesis and gliogenesis. J. Neurosci. 2007;27:12764–12774. doi: 10.1523/JNEUROSCI.3178-07.2007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Kohama T, Olivera A, Edsall L, Nagiec MM, Dickson R, Spiegel S. Molecular cloning and functional characterization of murine sphingosine kinase. J. Biol. Chem. 1998;273:23722–23728. doi: 10.1074/jbc.273.37.23722. [DOI] [PubMed] [Google Scholar]
  36. Kowalczyk A, Filipkowski RK, Rylski M, Wilczynski GM, Konopacki FA, Jaworski J, Ciemerych MA, Sicinski P, Kaczmarek L. The critical role of cyclin D2 in adult neurogenesis. J. Cell Biol. 2004;167:209–213. doi: 10.1083/jcb.200404181. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Knott SA, Nystrom PE, Andersson-Eklund L, Stern S, Marklund L, Andersson L, Haley CS. Approaches to interval mapping of QTL in multigeneration pedigree: the example of porcine chromosome 4. Anim. Genet. 2002;33:26–32. doi: 10.1046/j.1365-2052.2002.00803.x. [DOI] [PubMed] [Google Scholar]
  38. Lander ES, Botstein D. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics. 1989;121:185–199. doi: 10.1093/genetics/121.1.185. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Lauter N, Doebley J. Genetic variation for phenotypically invariant traits detected in teosinte: implications for the evolution of novel forms. Genetics. 2002;160:333–342. doi: 10.1093/genetics/160.1.333. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Lee AW, Emsley JG, Brown RE, Hagg T. Marked differences in olfactory sensitivity and apparent speed of forebrain neuroblast migration in three inbred strains of mice. Neuroscience. 2003;118:263–270. doi: 10.1016/s0306-4522(02)00950-8. [DOI] [PubMed] [Google Scholar]
  41. Lledo PM, Merkle FT, Alvarez-Buylla A. Origin and function of olfactory bulb interneuron diversity. Trends Neurosci. 2008;31:392–400. doi: 10.1016/j.tins.2008.05.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Liu HK, Belz T, Bock D, Takacs A, Wu H, Lichter P, Chai M, Schütz G. The nuclear receptor tailless is required for neurogenesis in the adult subventricular zone. Genes Dev. 2008;22:2473–2478. doi: 10.1101/gad.479308. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Lim DA, Tramontin AD, Trevejo JM, Herrera DG, Garcia-Verdugo JM, Alvarez-Buylla A. Noggin antagonizes BMP signalling to create a niche for adult neurogenesis. Neuron. 2000;28:713–726. doi: 10.1016/s0896-6273(00)00148-3. [DOI] [PubMed] [Google Scholar]
  44. Lois C, Alvarez-Buylla A. Long-distance neuronal migration in the adult mammalian brain. Science. 1994;264:1145–1148. doi: 10.1126/science.8178174. [DOI] [PubMed] [Google Scholar]
  45. Lu L, Wei L, Peirce JL, Wang X, Zhou J, Homayouni R, Williams RW, Airey DC. Using gene expression databases for classical trait QTL candidate gene discovery in the BXD recombinant inbred genetic reference population: mouse forebrain weight. BMC Genomics. 2008;9:444. doi: 10.1186/1471-2164-9-444. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Lu X, Sharkey L, Bartfai T. The brain galanin receptors: targets for novel antidepressant drugs. CNS Neurol. Disord. Drug Targets. 2007;6:183–192. doi: 10.2174/187152707780619335. [DOI] [PubMed] [Google Scholar]
  47. Ma J, Shan L, Yu LL, Yuan CG. Expression of galanin and galanin receptors in neurogenesis regions of adult mouse brain and effect of galanin on the neural stem cell's differentiation. Fen Zi Xi Bao Sheng Wu Xue Bao. 2008;41:359–366. [PubMed] [Google Scholar]
  48. Mandairon N, Sacquet J, Garcia S, Ravel N, Jourdan F, Didier A. Neurogenic correlates of an olfactory discrimination task in the adult olfactory bulb. Eur. J. Neurosci. 2006;24:3578–3588. doi: 10.1111/j.1460-9568.2006.05235.x. [DOI] [PubMed] [Google Scholar]
  49. Manichaikul A, Dupuis J, Sen S, Broman KW. Poor Performance of Bootstrap Confidence Intervals for the Location of a Quantitative Trait Locus. Genetics. 2006;174:481–489. doi: 10.1534/genetics.106.061549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Markwardt S, Overstreet-Wadiche L. GABAergic signalling to adult-generated neurons. J. Physiol. 2008;586:3745–3749. doi: 10.1113/jphysiol.2008.155713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Maysami S, Lan JQ, Minami M, Simon RP. Proliferating progenitor cells: a required cellular element for induction of ischemic tolerance in the brain. J. Cereb. Blood Flow Metab. 2008;28:1104–1113. doi: 10.1038/jcbfm.2008.4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Mazarati A, Lu X, Kilk K, Langel U, Wasterlain C, Bartfai T. Galanin type 2 receptors regulate neuronal survival, susceptibility to seizures and seizure-induced neurogenesis in the dentate gyrus. Eur. J. Neurosci. 2004;19:3235–3244. doi: 10.1111/j.0953-816X.2004.03449.x. [DOI] [PubMed] [Google Scholar]
  53. Meletis K, Wirta V, Hede SM, Nister M, Lundeberg J, Frisen J. p53 suppresses the self-renewal of adult neural stem cells. Development. 2006;133:363–369. doi: 10.1242/dev.02208. [DOI] [PubMed] [Google Scholar]
  54. Merkle FT, Mirzadeh Z, Alvarez-Buylla A. Mosaic organization of neural stem cells in the adult brain. Science. 2007;317:381–384. doi: 10.1126/science.1144914. [DOI] [PubMed] [Google Scholar]
  55. Merson TD, Dixon MP, Collin C, Rietze RL, Bartlett PF, Thomas T, Voss AK. The transcriptional coactivator Querkopf controls adult neurogenesis. J. Neurosci. 2006;26:11359–11370. doi: 10.1523/JNEUROSCI.2247-06.2006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Mizugishi K, Yamashita T, Olivera A, Miller GF, Spiegel S, Proia RL. Essential role for sphingosine kinases in neural and vascular development. Mol. Cell. Biol. 2005;25:11113–11121. doi: 10.1128/MCB.25.24.11113-11121.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Mudò G, Bonomo A, Di Liberto V, Frinchi M, Fuxe K, Belluardo N. The FGF-2/FGFRs neurotrophic system promotes neurogenesis in the adult brain. J. Neural Transm. 2009;116:995–1005. doi: 10.1007/s00702-009-0207-z. [DOI] [PubMed] [Google Scholar]
  58. Nowakowski RS, Lewin SB, Miller MW. Bromodeoxyuridine immunohistochemical determination of the lengths of the cell cycle and the DNA-synthetic phase for an anatomically defined population. J. Neurocytol. 1989;18:311–318. doi: 10.1007/BF01190834. [DOI] [PubMed] [Google Scholar]
  59. Palma V, Lim DA, Dahmane N, Sanchez P, Brionne TC, Herzberg CD, Gitton Y, Carleton A, Alvarez-Buylla A, Ruiz iAltaba A. Sonic hedgehog controls stem cell behavior in the postnatal and adult brain. Development. 2005;132:335–344. doi: 10.1242/dev.01567. [DOI] [PMC free article] [PubMed] [Google Scholar]
  60. Platel JC, Lacar B, Bordey A. GABA and glutamate signaling: homeostatic control of adult forebrain neurogenesis. J. Mol. Histol. 2007;38:303–311. doi: 10.1007/s10735-007-9103-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  61. Ramirez-Castillejo C, Sanchez-Sanchez F, Andreu-Agullo C, Ferron SR, Aroca-Aguilar JD, Sanchez P, Mira H, Escribano J, Farinas I. Pigment epithelium-derived factor is a niche signal for neural stem cell renewal. Nat. Neurosci. 2006;9:331–339. doi: 10.1038/nn1657. [DOI] [PubMed] [Google Scholar]
  62. Rochefort C, Gheusi G, Vincent J-D, Lledo P-M. Enriched odor exposure increases the number of newborn neurons in the adult olfactory bulb and improves odor memory. J. Neurosci. 2002;22:2679–2689. doi: 10.1523/JNEUROSCI.22-07-02679.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Rosen GD, Pung CJ, Owens CB, Caplow J, Kim H, Mozhui K, Lu L, Williams RW. Genetic modulation of striatal volume by loci on Chrs 6 and 17 in BXD recombinant inbred mice. Genes Brain Behav. 2009;8:296–308. doi: 10.1111/j.1601-183X.2009.00473.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  64. Seaberg RM, van der Kooy D. Adult rodent neurogenic regions: the ventricular subependyma contains neural stem cells, but the dentate gyrus contains restricted progenitors. J. Neurosci. 2002;22:1784–1793. doi: 10.1523/JNEUROSCI.22-05-01784.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  65. Schanzer A, Wachs FP, Wilhelm D, Acker T, Cooper-Kuhn C, Beck H, Winkler J, Aigner L, Plate KH, Kuhn HG. Direct stimulation of adult neural stem cells in vitro and neurogenesis in vivo by vascular endothelial growth factor. Brain Pathol. 2004;14:237–248. doi: 10.1111/j.1750-3639.2004.tb00060.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  66. Soria JM, Taglialatela P, Gil-Perotin S, Galli R, Gritti A, Verdugo JM, Bertuzzi S. Defective postnatal neurogenesis and disorganization of the rostral migratory stream in absence of the Vax1 homeobox gene. J. Neurosci. 2004;24:11171–11181. doi: 10.1523/JNEUROSCI.3248-04.2004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  67. Takahashi T, Nowakowski RS, Caviness VS., Jr The cell cycle of the pseudostratified ventricular epithelium of the embryonic murine cerebral wall. J. Neurosci. 1995;15:6046–6057. doi: 10.1523/JNEUROSCI.15-09-06046.1995. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Tanapat P, Hastings NB, Reeves AJ, Gould E. Estrogen stimulates a transient increase in the number of new neurons in the dentate gyrus of the adult female rat. J. Neurosci. 1999;19:5792–5801. doi: 10.1523/JNEUROSCI.19-14-05792.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Vanderluit JL, Ferguson KL, Nikoletopoulou V, Parker M, Ruzhynsky V, Alexson T, McNamara SM, Park DS, Rudnicki M, Slack RS. p107 regulates neuralprecursor cells in the mammalian brain. J. Cell Biol. 2004;166:853–863. doi: 10.1083/jcb.200403156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Wang S, Hashemi T, Fried S, Clemmons AL, Hawes BE. Differential intracellular signaling of the GalR1 and GalR2 galanin receptor subtypes. Biochemistry. 1998;37:6711–6717. doi: 10.1021/bi9728405. [DOI] [PubMed] [Google Scholar]
  71. Weller JI, Soller M, Brody T. Linkage Analysis of Quantitative Traits in an Interspecific Cross of Tomato (Lycopersicon Esculentum X Lycopersicon Pimpinellifolium) by Means of Genetic Markers. Genetics. 1998;118:329–339. doi: 10.1093/genetics/118.2.329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  72. Williams RW, Airey DC, Kulkarni A, Zhou G, Lu L. Genetic dissection of the olfactory bulbs of mice: QTLs on four chromosomes modulate bulb size. Behav Genet. 2001;31:61–77. doi: 10.1023/a:1010209925783. [DOI] [PubMed] [Google Scholar]
  73. Wittko IM, Schänzer A, Kuzmichev A, Schneider FT, Shibuya M, Raab S, Plate KH. VEGFR-1 regulates adult olfactory bulb neurogenesis and migration of neural progenitors in the rostral migratory stream in vivo. J. Neurosci. 2009;29:8704–8714. doi: 10.1523/JNEUROSCI.5527-08.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Zhao C, Deng W, Gage FH. Mechanisms and functional implications of adult neurogenesis. Cell. 2008;22:645–660. doi: 10.1016/j.cell.2008.01.033. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supp Fig s1. Fig. S1.

Comparison of two BrdU-labeled cell counting methods for quantifying proliferative cells in the RMS. (A) BrdU+ cell count from single best section containing a complete RMS extension from the lateral ventricle to the olfactory bulb significantly correlates with total BrdU+ cell count from 10 sections (80µm intervals) encompassing the entire medial to lateral extent of the RMS; P < 0.0001. (B) The linear density (BrdU+ cells/mm) calculated from a single best section also correlates with the total BrdU+ cell count determined from the 10 sections; P < 0.0001. Each data point represents counts obtained from a randomly selected recombinant inbred mouse.

NIHMS210978-supplement-Supp_Fig_s1.TIF (81.4KB, TIF)
Supp Fig s2. Fig. S2.

Schematical sagittal view of an adult mouse brain highlighting the four RMS representative segments (pink squares) selected for measuring the cell density and estimating the proliferative population in the RMS of A/J and C57BL/6J. All cells within these segments were counted and the corresponding areas were measured. The cell densities across all four regions were then averaged to give one value per animal. The general shape and trajectory of the RMS from the subventricular zone of the lateral ventricle (LV) to the olfactory bulb (OB) can be divided into three major components: vertical arm, the elbow, and the horizontal arm of the RMS.

NIHMS210978-supplement-Supp_Fig_s2.tif (317.3KB, tif)
Supp Fig s3. Fig. S3.

Age and sex did not influence the identification of RMS11a. (A) QTL Mapping for variation in the RMS linear density (BrdU+/mm) of RI strains ranging from 60-100 days old (n= 98; the original data contains animal ranged from 60-150 days). Genome scan LRS plot showed three suggestive QTL, one on Chr 11 (RMS11a), one on Chr 2, and another one on Chr 18. (B) QTL mapping for variation in the RMS linear density from adult female mice only (n= 83). Interval mapping also revealed a significant QTL mapped to RMS11a. (C) (D) are screenshots of the marker regression reports for mapping with narrowed age parameter and from mapping with female mice only. Trait value was consistently increased by theC57BL/6J allele represented by the negative additive effect value; whereas, the A/J allele is represented by positive additive effect value.

NIHMS210978-supplement-Supp_Fig_s3.tif (1.3MB, tif)
Supp Table s1. Table S1.

Signaling pathways and genes controlling the fate of adult neural stem cells and their progenitors. Information provided here was used for pathway analysis of QTL genes. Candidate genes were also assessed as to their interaction with genes known to regulate the cell cycle of adult neural progenitors.

NIHMS210978-supplement-Supp_Table_s1.doc (48KB, doc)

RESOURCES