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ABSTRACT: The current diagnosis of psychiatric disorders including major depressive disorder based largely on self-reported symptoms and clinical signs may be prone to patients' behaviors and psychiatrists' bias. This study aims at developing an unsupervised machine learning approach for the accurate identification of major depression based on single resting-state functional magnetic resonance imaging scans in the absence of clinical information. Twenty-four medication-naive patients with major depression and 29 demographically similar healthy individuals underwent resting-state functional magnetic resonance imaging. We first clustered the voxels within the perigenual cingulate cortex into two subregions, a subgenual region and a pregenual region, according to their distinct resting-state functional connectivity patterns and showed that a maximum margin clustering-based unsupervised machine learning approach extracted sufficient information from the subgenual cingulate functional connectivity map to differentiate depressed patients from healthy controls with a group-level clustering consistency of 92.5% and an individual-level classification consistency of 92.5%. It was also revealed that the subgenual cingulate functional connectivity network with the highest discriminative power primarily included the ventrolateral and ventromedial prefrontal cortex, superior temporal gyri and limbic areas, indicating that these connections may play critical roles in the pathophysiology of major depression. The current study suggests that subgenual cingulate functional connectivity network signatures may provide promising objective biomarkers for the diagnosis of major depression and that maximum margin clustering-based unsupervised machine learning approaches may have the potential to inform clinical practice and aid in research on psychiatric disorders. Hum Brain Mapp, 2013. © 2013 Wiley Periodicals, Inc.
Human Brain Mapping 04/2013; · 5.88 Impact Factor
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Hui Shen,
Jian Li,
Jigang Zhang,
Chao Xu,
Yan Jiang,
Zikai Wu,
Fuping Zhao,
Li Liao,
Jun Chen,
Yong Lin,
Qing Tian,
Christopher J Papasian,
Hong-Wen Deng
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ABSTRACT: Whole genome sequencing studies are essential to obtain a comprehensive understanding of the vast pattern of human genomic variations. Here we report the results of a high-coverage whole genome sequencing study for 44 unrelated healthy Caucasian adults, each sequenced to over 50-fold coverage (averaging 65.8×). We identified approximately 11 million single nucleotide polymorphisms (SNPs), 2.8 million short insertions and deletions, and over 500,000 block substitutions. We showed that, although previous studies, including the 1000 Genomes Project Phase 1 study, have catalogued the vast majority of common SNPs, many of the low-frequency and rare variants remain undiscovered. For instance, approximately 1.4 million SNPs and 1.3 million short indels that we found were novel to both the dbSNP and the 1000 Genomes Project Phase 1 data sets, and the majority of which (∼96%) have a minor allele frequency less than 5%. On average, each individual genome carried ∼3.3 million SNPs and ∼492,000 indels/block substitutions, including approximately 179 variants that were predicted to cause loss of function of the gene products. Moreover, each individual genome carried an average of 44 such loss-of-function variants in a homozygous state, which would completely "knock out" the corresponding genes. Across all the 44 genomes, a total of 182 genes were "knocked-out" in at least one individual genome, among which 46 genes were "knocked out" in over 30% of our samples, suggesting that a number of genes are commonly "knocked-out" in general populations. Gene ontology analysis suggested that these commonly "knocked-out" genes are enriched in biological process related to antigen processing and immune response. Our results contribute towards a comprehensive characterization of human genomic variation, especially for less-common and rare variants, and provide an invaluable resource for future genetic studies of human variation and diseases.
PLoS ONE 01/2013; 8(4):e59494. · 4.09 Impact Factor
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Shu Ran,
Yu-Fang Pei,
Yong-Jun Liu,
Lei Zhang,
Ying-Ying Han,
Rong Hai,
Qing Tian,
Yong Lin,
Tie-Lin Yang,
Yan-Fang Guo, Hui Shen,
Inderpal S Thethi,
Xue-Zhen Zhu,
Hong-Wen Deng
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ABSTRACT: Femoral neck geometric parameters (FNGPs), which include cortical thickness (CT), periosteal diameter (W), buckling ratio (BR), cross-sectional area (CSA), and section modulus (Z), contribute to bone strength and may predict hip fracture risk. Age at menarche (AAM) is an important risk factor for osteoporosis and bone fractures in women. Some FNGPs are genetically correlated with AAM. In this study, we performed a bivariate genome-wide association study (GWAS) to identify new candidate genes responsible for both FNGPs and AAM. In the discovery stage, we tested 760,794 SNPs in 1,728 unrelated Caucasian subject, followed by replication analyses in independent samples of US Caucasians (with 501 subjects) and Chinese (with 826 subjects). We found six SNPs that were associated with FNGPs and AAM. These SNPs are located in three genes (i.e. NRCAM, IDS and LOC148145), suggesting these three genes may co-regulate FNGPs and AAM. Our findings may help improve the understanding of genetic architecture and pathophysiological mechanisms underlying both osteoporosis and AAM.
PLoS ONE 01/2013; 8(4):e60362. · 4.09 Impact Factor
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ABSTRACT: BACKGROUND: Previous studies have suggested that the default mode network (DMN) plays a central role in the physiopathology of major depressive disorder (MDD). However, the effect of antidepressant treatment on functional connectivity within the DMN has yet to be established. Considering the very high rates of relapse in recovered subjects, we hypothesized that abnormalities in DMN functional connectivity would persist in recovered MDD subjects. METHODS: Resting state functional magnetic resonance imaging images were collected from 24 MDD patients and 29 healthy control subjects. After 12 weeks of antidepressant treatment, 18 recovered MDD subjects were scanned again. Group independent component analysis was performed to decompose the resting state images into spatially independent components. Default mode subnetworks were identified using a template based on previous studies. Group differences in the ensuing subnetworks were tested using two-sample t tests. RESULTS: Two spatially independent default mode subnetworks were detected in all subjects: the anterior subnetwork and the posterior subnetwork. Both subnetworks showed increased functional connectivity in pretreatment MDD subjects, relative to control subjects. Differences in the posterior subnetwork were normalized after antidepressant treatment, while abnormal functional connectivity persisted within the anterior subnetwork. CONCLUSIONS: Our findings suggest a dissociation of the DMN into subnetworks, where persistent abnormal functional connectivity within the anterior subnetwork in recovered MDD subjects may constitute a biomarker of asymptomatic depression and potential for relapse.
Biological psychiatry 12/2012; · 8.93 Impact Factor
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ABSTRACT: In recent years, the cerebellum has been demonstrated to be involved in cognitive control and emotional processing and to play an important role in the pathology of major depressive disorder (MDD). The current study aims to explore the potential utility of selecting the altered cerebellar-cerebral functional connectivity as a classification feature to discriminate depressed patients from healthy controls. Twenty-four medication-free patients with major depression and 29 matched, healthy controls underwent resting-state functional magnetic resonance imaging. A promising classification accuracy of 90.6% was achieved using resting-state functional connectivity between predefined cerebellar seed regions and the voxels within the cerebrum as features. Moreover, the most discriminating functional connections were mainly located between the cerebellum and the anterior cingulate cortex, the ventromedial prefrontal cortex, the ventrolateral prefrontal cortex, the temporal lobe and the fusiform gyrus, which may contribute to the emotional and cognitive impairments observed in major depression. The current findings imply that the cerebellum might be considered a node in the distributed disease-related brain network in major depression.
Brain research 12/2012; · 2.46 Impact Factor
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ABSTRACT: Bone size (BS) contributes significantly to the risk of osteoporotic fracture. Osteoporotic spine fracture is one of the most disabling outcomes of osteoporosis. This study aims to identify genomic loci underlying spine BS variation in humans. We performed a genome-wide association scan in 2,286 unrelated Caucasians using Affymetrix 6.0 SNP arrays. Areal BS (cm(2)) at lumbar spine was measured using dual energy X-ray absorptiometry scanners. SNPs of interest were subjected to replication analyses and meta-analyses with additional two independent Caucasian populations (N = 1,000 and 2,503) and one Chinese population (N = 1,627). In the initial GWAS, 91 SNPs were associated with spine BS (P<1.0E-4). Eight contiguous SNPs were found clustering in a haplotype block within UQCC gene (ubiquinol-cytochrome creductase complex chaperone). Association of the above eight SNPs with spine BS were replicated in one Caucasian and one Chinese populations. Meta-analyses (N = 7,416) generated much stronger association signals for these SNPs (e.g., P = 1.86E-07 for SNP rs6060373), supporting association of UQCC with spine BS across ethnicities. This study identified a novel locus, i.e., the UQCC gene, for spine BS variation in humans. Future functional studies will contribute to elucidating the mechanisms by which UQCC regulates bone growth and development.
Bone 11/2012; · 4.02 Impact Factor
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Tie-Lin Yang,
Yan Guo, Hui Shen,
Jian Li,
Joseph T Glessner,
Chuan Qiu,
Fei-Yan Deng,
Qing Tian,
Ping Yu,
Yao-Zhong Liu,
Yong-Jun Liu,
Hakon Hakonarson,
Struan F A Grant,
Hong-Wen Deng
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ABSTRACT: Background:Obesity is a highly heritable disease defined by high body mass index (BMI). However, a large proportion of the heritability of obesity remains unexplained. Copy number variations (CNVs) might contribute to the missing heritability of obesity.Methods:We conducted genome-wide CNV analyses on obesity phenotypes, including BMI and body fat mass in a discovery sample of 2215 unrelated white subjects. After quality control, 314 CNVs were used for association tests. For significant CNVs identified, follow-up replication analyses were performed in three independent samples, including an unrelated sample of 1000 white subjects (OM sample), a family-based sample of 8385 white subjects (FHS sample), and an African-American sample of 1479 obesity cases and 1575 lean controls (AA sample).Results:Genome-wide CNV analyses detected that a CNV located at 10q26.3, which, even after multiple testing corrections, showed a strong association with both BMI (P = 2.30 × 10(-4), β = 2.164) and body fat mass (P = 6.76 × 10(-5), β = 4.126). This CNV was successfully replicated in the three replication samples (OM sample: P = 0.0465 for BMI, 0.0435 for fat mass; FHS sample: P = 0.0038 for BMI; AA sample: P = 0.0023 for obesity). Quantitative PCR validated this CNV, which covers a gene, CYP2E1. The protein encoded by CYP2E1 involves the synthesis of cholesterol, steroids and other lipids, which may have a potential impact on obesity.Conclusion:Our findings suggest the significant contribution of CNV10q26.3 to the pathogenesis of obesity.
The Journal of clinical endocrinology and metabolism 11/2012; · 6.50 Impact Factor
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Tie-Lin Yang,
Yan Guo,
Jian Li,
Lei Zhang, Hui Shen,
Siyang M Li,
Siyuan K Li,
Qing Tian,
Yong-Jun Liu,
Christopher J Papasian,
Hong-Wen Deng
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ABSTRACT: Osteoporosis is characterized by low bone mineral density (BMD), a highly heritable trait that is determined, in part, by the actions and interactions of multiple genes. While an increasing number of genes have been identified to have independent effects on BMD, few studies have been performed to identify genes that interact with one another to affect BMD. In this study, we performed gene-gene interaction analyses in selected candidate genes in individuals with extremely high vs. low hip BMD (20% tails of the distributions), in two independent US Caucasian samples. The first sample contained 916 unrelated subjects with extreme hip BMD Z-scores selected from a population composed of 2,286 subjects. The second sample consisted of 400 unrelated subjects with extreme hip BMD Z-scores selected from a population composed of 1,000 subjects. Combining results from these two samples, we found one interacting gene pair (RBMS3 vs. ZNF516) which, even after Bonferroni correction for multiple testing, showed consistently significant effects on hip BMD. RMBS3 harbored two SNPs, rs6549904 and rs7640046, both of which had significant interactions with a SNP, rs4891159, located on ZNF516 (P values: 7.04×10(-11) and 1.03×10(-10) ). We further validated these results in two additional samples of Caucasian and African descent. The gene pair, RBMS3 vs. ZNF516, was successfully replicated in the Caucasian sample (P values: 8.07×10(-3) and 2.91×10(-3) ). For the African sample, a significant interaction was also detected (P values: 0.031 and 0.043), but the direction of the effect was opposite to that observed in the three Caucasian samples. By providing evidence for genetic interactions underlying BMD, this study further delineated the genetic architecture of osteoporosis. © 2012 American Society for Bone and Mineral Research.
Journal of bone and mineral research: the official journal of the American Society for Bone and Mineral Research 10/2012; · 6.04 Impact Factor
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Yingying Han,
Yufang Pei,
Yaozhong Liu,
Lei Zhang,
Shuyan Wu,
Qing Tian,
Xiangding Chen, Hui Shen,
Xuezhen Zhu,
Christopher J Papasian,
Hongwen Deng
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ABSTRACT: Compressive strength index (CSI) is a newly established index for predicting hip fracture, the most serious consequence of osteoporosis. Appendicular lean mass (ALM), which influences skeletal strength of the lower limbs, is another trait associated with the risk of hip fracture. In this study, we performed a bivariate genome-wide association study (GWAS) to identify new candidate genes responsible for both CSI and ALM. In our discovery sample of 1627 unrelated Chinese subjects (802 males and 825 females), we scanned 909,509 SNPs using the Affymetrix Human Genome SNP 6.0 genotyping array. We successfully replicated our results in a sample of 2286 Caucasian subjects (558 males and 1728 females). The results indicated that five SNPs (rs174583, rs174577, rs174549, rs174548, rs7672337) in the FADS1, FADS2, and DCHS2 genes had significant bivariate associations with CSI and ALM in male subjects for both the GWAS discovery (with P<8.42×10(-6)) and the Caucasian sample (with P<0.07). We performed further replication analysis in a 2nd Caucasian sample with 501 Caucasian male subjects, using Affymetrix 500k arrays, and found that two of the above SNPs (rs174548 and rs174549, P=0.07) had bivariate associations with both CSI and ALM in males; the other 3 SNPs were not typed with the 500k array. The above findings suggest that the 3 genes, FADS1, FADS2, and DCHS2, containing these SNPs might play dual roles influencing both CSI and ALM in males. Our findings provide new insights into our understanding of the genetic basis of bone metabolism and the pathogenesis of osteoporosis.
Bone 08/2012; 51(6):1000-7. · 4.02 Impact Factor
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ABSTRACT: Context:Menarche is a significant physiological event for women. Age at menarche (AAM) is a heritable trait associated with many common female diseases. The genetic basis and the mechanism for AAM are largely unknown. Copy number variation (CNV) is a common type of genetic variation underlying human complex traits. The importance of CNV to AAM variation is unclear.Objective:The objective of the study was to identify CNV important to AAM variation.Design:We performed the first genome-wide CNV study of AAM in 1654 Caucasian females using Affymetrix human single-nucleotide polymorphism 6.0 array. We also replicated our findings in another Chinese cohort containing 752 women.Results:We identified a CNV, variation_38399, in the 2q14.2 region, for association with AAM (P = 1.03 × 10(-3)). The CNV has two variants (one copy and two copy), with a mean AAM of 14.00 yr and 12.90 yr, respectively. Interestingly, in a Chinese sample containing 752 women, this CNV has been replicated both with a marginally significant P = 0.090 and with a same direction of effect (a lower copy number for a later AAM). The CNV is located approximately 75 kb upstream of the diazepam binding inhibitor (DBI), a gene known to regulate estrogen levels, a key factor for menarche.Conclusion:Our findings for the first time identified a novel CNV and suggested the DBI-mediated endocrinological pathway as a potential mechanism for AAM regulation.
The Journal of clinical endocrinology and metabolism 08/2012; · 6.50 Impact Factor
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ABSTRACT: Lean body mass (LBM) and age at menarche (AAM) are two important complex traits for human health. The aim of this study was to identify pleiotropic genes for both traits using a powerful bivariate genome-wide association study (GWAS). Two studies, a discovery study and a replication study, were performed. In the discovery study, 909622 single nucleotide polymorphisms (SNPs) were genotyped in 801 unrelated female Han Chinese subjects using the Affymetrix human genome-wide SNP array 6.0 platform. Then, a bivariate GWAS was performed to identify the SNPs that may be important for LBM and AAM. In the replication study, significant findings from the discovery study were validated in 1692 unrelated Caucasian female subjects. One SNP rs3027009 that was bivariately associated with left arm lean mass and AAM in the discovery samples (P=7.26×10(-6)) and in the replication samples (P=0.005) was identified. The SNP is located at the upstream of DARC (Duffy antigen receptor for chemokines) gene, suggesting that DARC may play an important role in regulating the metabolisms of both LBM and AAM.
Science China. Life sciences 06/2012; 55(6):516-20. · 2.02 Impact Factor
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ABSTRACT: The surface morphology of quasi-periodic stripe-shaped patterns of magnetite fluids was observed in applied perpendicular
magnetic fields by means of scanning electron microscopy. The nanoparticles of the magnetite fluids are arranged in oriental
quasilinear chains in applied perpendicular magnetic fields as observed using transmission electron microscopy. This arrangement
results from particle-particle interactions and particle-carrier liquids interactions, which are eventually controlled by
the magnetic fields distribution.
Science in China Series E Technological Sciences 05/2012; 46(2):168-172. · 1.02 Impact Factor
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ABSTRACT: Several meta-analyses were recently conducted in attempts to identify the core brain regions exhibiting pathological changes
in schizophrenia, which could potentially act as disease markers. Based on the findings of these meta-analyses, we developed
a multivariate pattern analysis method to classify schizophrenic patients and healthy controls using structural magnetic resonance
imaging (sMRI) data. Independent component analysis (ICA) was used to decompose gray matter density images into a set of spatially
independent components. Spatial multiple regression of a region of interest (ROI) mask with each of the components was then
performed to determine pathological patterns, in which the voxels were taken as features for classification. After dimensionality
reduction using principal component analysis (PCA), a nonlinear support vector machine (SVM) classifier was trained to discriminate
schizophrenic patients from healthy controls. The performance of the classifier was tested using a 10-fold cross-validation
strategy. Experimental results showed that two distinct spatial patterns displayed discriminative power for schizophrenia,
which mainly included the prefrontal cortex (PFC) and subcortical regions respectively. It was found that simultaneous usage
of these two patterns improved the classification performance compared to using either of them alone. Moreover, the two pathological
patterns constitute a prefronto-subcortical network, suggesting that schizophrenia involves abnormalities in networks of brain
regions.
Keywordsschizophrenia–discriminative analysis–gray matter network–independent component analysis (ICA)–support vector machine (SVM)
Frontiers of Electrical and Electronic Engineering in China 04/2012; 6(2):353-362.
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ABSTRACT: There has been growing interest recently in the use of multivariate pattern analysis (MVPA) to decode information from high-dimensional neuroimaging data. The present study employed a support vector machine-based MVPA approach to identify the complex patterns of sex differences in brain structure and resting-state function. We also aimed to assess the role of anatomy on functional sex differences during rest. One hundred and forty healthy young Chinese adults (70 men and 70 women) underwent structural and resting-state functional MRI scans. Gray matter density and regional homogeneity (ReHo) were used to map brain structure and resting-state function, respectively. After combining these two feature vectors into one union-vector, a pattern classifier was designed using principal component analysis and linear support vector machine to identify brain areas that had distinct characteristics between the groups. We found that: (1) male and female brains were different with a mean classification accuracy of 89%; (2) sex differences in gray matter density were widely distributed in the brain, notably in the occipital lobe and the cerebellum; (3) men primarily showed higher ReHo in their right hemispheres and women tended to show greater ReHo in their left hemispheres; (4) about 50% of brain areas with functional sex differences exhibited significant positive correlations between gray matter density and ReHo. Our results suggest that sex is an important factor that account for interindividual variability in the healthy brain.
NeuroImage 04/2012; 61(4):931-40. · 5.89 Impact Factor
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ABSTRACT: Recent resting-state functional connectivity magnetic resonance imaging studies have shown significant group differences in several regions and networks between patients with major depressive disorder and healthy controls. The objective of the present study was to investigate the whole-brain resting-state functional connectivity patterns of depressed patients, which can be used to test the feasibility of identifying major depressive individuals from healthy controls. Multivariate pattern analysis was employed to classify 24 depressed patients from 29 demographically matched healthy volunteers. Permutation tests were used to assess classifier performance. The experimental results demonstrate that 94.3% (P < 0.0001) of subjects were correctly classified by leave-one-out cross-validation, including 100% identification of all patients. The majority of the most discriminating functional connections were located within or across the default mode network, affective network, visual cortical areas and cerebellum, thereby indicating that the disease-related resting-state network alterations may give rise to a portion of the complex of emotional and cognitive disturbances in major depression. Moreover, the amygdala, anterior cingulate cortex, parahippocampal gyrus and hippocampus, which exhibit high discriminative power in classification, may play important roles in the pathophysiology of this disorder. The current study may shed new light on the pathological mechanism of major depression and suggests that whole-brain resting-state functional connectivity magnetic resonance imaging may provide potential effective biomarkers for its clinical diagnosis.
Brain 03/2012; 135(Pt 5):1498-507. · 9.46 Impact Factor
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ABSTRACT: Increased plasmalemmal localization of α4βδ GABA(A) receptors (GABARs) occurs in the hippocampal pyramidal cells of female mice at pubertal onset (Shen et al., 2010). This increase occurs on both dendritic spines and shafts of CA1 pyramidal cells and is in response to hormone fluctuations that occur at pubertal onset. However, little is known about how the α4 and δ subunits individually mediate the formation of functional, plasmalemmal α4βδ GABARs. To determine whether expression of the α4 subunit is necessary for plasmalemmal δ subunit localization at pubertal onset, electron microscopic-immunocytochemistry (EM-ICC) was employed. CA1 pyramidal cells of female α4 knockout (KO) mice were tested for plasmalemmal levels of the δ subunit within dendritic spine and shaft profiles at the onset of puberty. EM-ICC revealed that the α4 and δ subunits localize on dendritic spines and shafts at sites extrasynaptic to GABAergic input at pubertal onset in tissue of wild-type (WT) mice. At pubertal onset, plasmalemmal localization of the δ subunit is reduced 45.9% on dendritic spines, and 56.7% on dendritic shafts with KO of the α4 subunit, as compared to WT tissue, yet levels of intracellular δ immunoreactivity remain unchanged. The decline in plasmalemmal localization is manifested as decreased responsiveness to the GABA agonist gaboxadol at concentrations that are selective for δ-containing GABARs. Additionally, α4 KO mice have larger dendritic spine and shaft profiles. Our findings demonstrate that α4 subunit expression strongly influences the pubertal increase of δ subunits at the plasma membrane, and that genetic deletion of α4 serves as a functional knock-down of δ-containing GABARs.
Brain research 02/2012; 1450:11-23. · 2.46 Impact Factor
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ABSTRACT: Psychological stress (PS) could cause decreased iron absorption and iron redistribution in body resulting in low iron concentration in the bone marrow and inhibition of erythropoiesis. In the present study, we investigated the effect of zinc supplementation on the iron metabolism, erythropoiesis, and oxidative stress status in PS-induced rats. Thirty-two rats were divided into two groups randomly: control group and zinc supplementation group. Each group was subdivided into two subgroups: control group and PS group. Rats received zinc supplementation before PS exposure established by a communication box. We investigated the serum corticosterone (CORT) level; iron apparent absorption; iron contents in liver, spleen, cortex, hippocampus, striatum, and serum; hematological parameters; malondialdehyde (MDA); reduced glutathione (GSH); and superoxide dismutase (SOD). Compared to PS-treated rats with normal diet, the PS-treated rats with zinc supplementation showed increased iron apparent absorption, serum iron, hemoglobin, red blood cell, GSH, and SOD activities; while the serum CORT; iron contents in liver, spleen, and regional brain; and MDA decreased. These results indicated that dietary zinc supplementation had preventive effects against PS-induced iron dyshomeostasis, erythropoiesis inhibition, and oxidative stress status in rats.
Biological trace element research 01/2012; 147(1-3):285-91. · 1.92 Impact Factor
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Dermatologic Surgery 01/2012; 38(5):813-5. · 1.80 Impact Factor
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Chunxiang Fu,
Ramanjulu Sunkar,
Chuanen Zhou, Hui Shen,
Ji-Yi Zhang,
Jessica Matts,
Jennifer Wolf,
David G J Mann,
C Neal Stewart,
Yuhong Tang,
Zeng-Yu Wang
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ABSTRACT: Switchgrass (Panicum virgatum L.) has been developed into a dedicated herbaceous bioenergy crop. Biomass yield is a major target trait for genetic improvement of switchgrass. microRNAs have emerged as a prominent class of gene regulatory factors that has the potential to improve complex traits such as biomass yield. A miR156b precursor was overexpressed in switchgrass. The effects of miR156 overexpression on SQUAMOSA PROMOTER BINDING PROTEIN LIKE (SPL) genes were revealed by microarray and quantitative RT-PCR analyses. Morphological alterations, biomass yield, saccharification efficiency and forage digestibility of the transgenic plants were characterized. miR156 controls apical dominance and floral transition in switchgrass by suppressing its target SPL genes. Relatively low levels of miR156 overexpression were sufficient to increase biomass yield while producing plants with normal flowering time. Moderate levels of miR156 led to improved biomass but the plants were non-flowering. These two groups of plants produced 58%-101% more biomass yield compared with the control. However, high miR156 levels resulted in severely stunted growth. The degree of morphological alterations of the transgenic switchgrass depends on miR156 level. Compared with floral transition, a lower miR156 level is required to disrupt apical dominance. The improvement in biomass yield was mainly because of the increase in tiller number. Targeted overexpression of miR156 also improved solubilized sugar yield and forage digestibility, and offered an effective approach for transgene containment.
Plant Biotechnology Journal 01/2012; 10(4):443-52. · 5.44 Impact Factor
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ABSTRACT: Numerous studies have demonstrated the higher-order functions of the cerebellum, including emotion regulation and cognitive processing, and have indicated that the cerebellum should therefore be included in the pathophysiological models of major depressive disorder. The aim of this study was to compare the resting-state functional connectivity of the cerebellum in adults with major depression and healthy controls.
Twenty adults with major depression and 20 gender-, age-, and education-matched controls were investigated using seed-based resting-state functional connectivity magnetic resonance imaging.
Compared with the controls, depressed patients showed significantly increased functional connectivity between the cerebellum and the temporal poles. However, significantly reduced cerebellar functional connectivity was observed in the patient group in relation to both the default-mode network, mainly including the ventromedial prefrontal cortex and the posterior cingulate cortex/precuneus, and the executive control network, mainly including the superior frontal cortex and orbitofrontal cortex. Moreover, the Hamilton Depression Rating Scale score was negatively correlated with the functional connectivity between the bilateral Lobule VIIb and the right superior frontal gyrus in depressed patients.
This study demonstrated increased cerebellar coupling with the temporal poles and reduced coupling with the regions in the default-mode and executive control networks in adults with major depression. These differences between patients and controls could be associated with the emotional disturbances and cognitive control function deficits that accompany major depression. Aberrant cerebellar connectivity during major depression may also imply a substantial role for the cerebellum in the pathophysiological models of depression.
PLoS ONE 01/2012; 7(6):e39516. · 4.09 Impact Factor
