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Basit A, Lim KB. Systematic approach of polyploidy as an evolutionary genetic and genomic phenomenon in horticultural crops. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2024; 348:112236. [PMID: 39186951 DOI: 10.1016/j.plantsci.2024.112236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 08/15/2024] [Accepted: 08/18/2024] [Indexed: 08/28/2024]
Abstract
Polyploidy is thought to be an evolutionary and systematic mechanism for gene flow and phenotypic advancement in flowering plants. It is a natural phenomenon that promotes diversity by creating new permutations enhancing the prime potentials as compared to progenitors. Two different pathways have been recognized in studying polyploidy in nature; mitotic or somatic chromosome doubling and cytogenetics variation. Secondly, the vital influence of being polyploid is its heritable property (unreduced reproductive cells) formed during first and second-division restitution (FDR & SDR). Different approaches either chemical (Colchicine, Oryzalin, Caffeine, Trifuralin, or phosphoric amides) or gaseous i.e. Nitrous oxide have been deliberated as strong polyploidy causing agents. A wide range of cytogenetic practices like chromosomes study, ploidy, genome analysis, and plant morphology and anatomy have been studied in different plant species. Flow cytometry for ploidy and chromosome analysis through fluorescence and genomic in situ hybridization (FISH & GISH) are the basic methods to evaluate heredity substances sampled from leaves and roots. Many horticultural crops have been developed successfully and released commercially for consumption. Moreover, some deep detailed studies are needed to check the strong relationship between unique morphological features and genetic makeup concerning genes and hormonal expression in a strong approach.
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Affiliation(s)
- Abdul Basit
- Department of Horticultural Science, Kyungpook National University, Daegu 41566, South Korea.
| | - Ki-Byung Lim
- Department of Horticultural Science, Kyungpook National University, Daegu 41566, South Korea; Institute of Agricultural Science and Technology, Kyungpook National University, Daegu, South Korea.
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2
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Sun B, Li S, Pi Z, Wu Z, Wang R. Assessment of Genetic Diversity and Population Structure of Exotic Sugar Beet ( Beta vulgaris L.) Varieties Using Three Molecular Markers. PLANTS (BASEL, SWITZERLAND) 2024; 13:2954. [PMID: 39519873 PMCID: PMC11548155 DOI: 10.3390/plants13212954] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Revised: 10/20/2024] [Accepted: 10/21/2024] [Indexed: 11/16/2024]
Abstract
Sugar beet (Beta vulgaris L.) is a biennial herb belonging to the Amaranthaceae family. It contributes to approximately 30% of the world's total sucrose production and is an economically important crop. In this study, we analyzed the genetic diversity and population structure of 132 exotic sugar beet varieties using three molecular makers: four pairs of simple sequence repeat (SSR) primers, three pairs of insertion-deletion sequence (InDel) primers, and 20 cis-element amplification polymorphism (CEAP) primers. The results indicated that the number of alleles (Na) was 298, among which the number of effective alleles (Ne) was 182.426 (accounting for approximately 61.2%). The mean value of the genetic diversity index was 0.836. The polymorphic information content (PIC) was 0.639-0.907 (mean = 0.819), indicating a high level of polymorphism. These sugar beet varieties were classified into six clusters using the UPGMA method of cluster analysis. Population structure analysis revealed that the most ideal K value was 6. This indicated that the test materials could be divided into six categories, consistent with the clustering results. The clustering results indicated that most sugar beet varieties from the same breeding company clustered together, and the genetic distance between them was small, indicating that they may share the same male and/or female parent. Some varieties from different companies clustered together, indicating a narrow genetic base and potential exchange of germplasm resources between breeding companies. This study revealed the genetic differences among exotic sugar beet varieties and characteristics of the population structure. It provided a scientific basis for the identification of sugar beet varieties and markers-assisted breeding in China in the future.
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Affiliation(s)
- Bowei Sun
- Academy of Modern Agriculture and Ecological Environment, Heilongjiang University, Harbin 150080, China; (B.S.); (S.L.); (Z.P.)
| | - Shengnan Li
- Academy of Modern Agriculture and Ecological Environment, Heilongjiang University, Harbin 150080, China; (B.S.); (S.L.); (Z.P.)
| | - Zhi Pi
- Academy of Modern Agriculture and Ecological Environment, Heilongjiang University, Harbin 150080, China; (B.S.); (S.L.); (Z.P.)
| | - Zedong Wu
- Academy of Modern Agriculture and Ecological Environment, Heilongjiang University, Harbin 150080, China; (B.S.); (S.L.); (Z.P.)
| | - Ronghua Wang
- Shihezi Academy of Agricultural Sciences, Shihezi 832061, China
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3
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Trifonova AA, Paradnya ER, Boris KV, Kudryavtsev AM. NBS-LRR Resistance Genes Polymorphism of Sugar Beet Hybrids according to NBS-Profiling Data. RUSS J GENET+ 2022. [DOI: 10.1134/s1022795422010112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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4
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In silico identification of long non-coding RNA based simple sequence repeat markers and their application in diversity analysis in rice. GENE REPORTS 2019. [DOI: 10.1016/j.genrep.2019.100418] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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5
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Skorupa M, Gołębiewski M, Kurnik K, Niedojadło J, Kęsy J, Klamkowski K, Wójcik K, Treder W, Tretyn A, Tyburski J. Salt stress vs. salt shock - the case of sugar beet and its halophytic ancestor. BMC PLANT BIOLOGY 2019; 19:57. [PMID: 30727960 PMCID: PMC6364445 DOI: 10.1186/s12870-019-1661-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Accepted: 01/24/2019] [Indexed: 05/20/2023]
Abstract
BACKGROUND Sugar beet is a highly salt-tolerant crop. However, its ability to withstand high salinity is reduced compared to sea beet, a wild ancestor of all beet crops. The aim of this study was to investigate transcriptional patterns associated with physiological, cytological and biochemical mechanisms involved in salt response in these closely related subspecies. Salt acclimation strategies were assessed in plants subjected to either gradually increasing salt levels (salt-stress) or in excised leaves, exposed instantly to salinity (salt-shock). RESULT The majority of DEGs was down-regulated under stress, which may lead to certain aspects of metabolism being reduced in this treatment, as exemplified by lowered transpiration and photosynthesis. This effect was more pronounced in sugar beet. Additionally, sugar beet, but not sea beet, growth was restricted. Silencing of genes encoding numerous transcription factors and signaling proteins was observed, concomitantly with the up-regulation of lipid transfer protein-encoding genes and those coding for NRTs. Bark storage protein genes were up-regulated in sugar beet to the level observed in unstressed sea beet. Osmotic adjustment, manifested by increased water and proline content, occurred in salt-shocked leaves of both genotypes, due to the concerted activation of genes encoding aquaporins, ion channels and osmoprotectants synthesizing enzymes. bHLH137 was the only TF-encoding gene induced by salt in a dose-dependent manner irrespective of the mode of salt treatment. Moreover, the incidence of bHLH-binding motives in promoter regions of salinity-regulated genes was significantly greater than in non-regulated ones. CONCLUSIONS Maintaining homeostasis under salt stress requires deeper transcriptomic changes in the sugar beet than in the sea beet. In both genotypes salt shock elicits greater transcriptomic changes than stress and it results in greater number of up-regulated genes compared to the latter. NRTs and bark storage protein may play a yet undefined role in salt stress-acclimation in beet. bHLH is a putative regulator of salt response in beet leaves and a promising candidate for further studies.
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Affiliation(s)
- Monika Skorupa
- Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń, Poland
| | - Marcin Gołębiewski
- Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń, Poland
- Chair of Plant Physiology and Biotechnology, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Toruń, Poland
| | - Katarzyna Kurnik
- Chair of Plant Physiology and Biotechnology, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Toruń, Poland
| | - Janusz Niedojadło
- Department of Cellular and Molecular Biology, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Toruń, Poland
| | - Jacek Kęsy
- Chair of Plant Physiology and Biotechnology, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Toruń, Poland
| | | | | | | | - Andrzej Tretyn
- Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń, Poland
- Chair of Plant Physiology and Biotechnology, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Toruń, Poland
| | - Jarosław Tyburski
- Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń, Poland
- Chair of Plant Physiology and Biotechnology, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Toruń, Poland
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6
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Osman WM, Jelinek HF, Tay GK, Khandoker AH, Khalaf K, Almahmeed W, Hassan MH, Alsafar HS. Clinical and genetic associations of renal function and diabetic kidney disease in the United Arab Emirates: a cross-sectional study. BMJ Open 2018; 8:e020759. [PMID: 30552240 PMCID: PMC6303615 DOI: 10.1136/bmjopen-2017-020759] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVES Within the Emirati population, risk factors and genetic predisposition to diabetic kidney disease (DKD) have not yet been investigated. The aim of this research was to determine potential clinical, laboratory and reported genetic loci as risk factors for DKD. RESEARCH DESIGN AND METHODS Four hundred and ninety unrelated Emirati nationals with type 2 diabetes mellitus (T2DM) were recruited with and without DKD, and clinical and laboratory data were obtained. Following adjustments for possible confounders, a logistic regression model was developed to test the associations of 63 single nucleotide polymorphisms (SNPs) in 43 genetic loci with DKD (145 patients with DKD and 265 without DKD). Linear regression models, adjusted for age and gender, were then used to study the genetic associations of five renal function traits, including 83 SNPs with albumin-to-creatinine ratio, 92 SNPs with vitamin D (25-OH cholecalciferol), 288 SNPs with estimated glomerular filtration rate (eGFR), 363 SNPs with serum creatinine and 73 SNPs with blood urea. RESULTS Patients with DKD, as compared with those without the disease, were mostly men (52%vs38% for controls), older (67vs59 years) and had significant rates of hypertension and dyslipidaemia. Furthermore, patients with DKD had T2DM for a longer duration of time (16vs10 years), which in an additive manner was the single factor that significantly contributed to the development of DKD (p=0.02, OR=3.12, 95% CI 1.21 to 8.02). Among the replicated associations of the genetic loci with different renal function traits, the most notable included SHROOM3 with levels of serum creatinine, eGFR and DKD (Padjusted=0.04, OR=1.46); CASR, GC and CYP2R1 with vitamin D levels; as well as WDR72 with serum creatinine and eGFR levels. CONCLUSIONS Associations were found between several genetic loci and risk markers for DKD, which may influence kidney function traits and DKD in a population of Arab ancestry.
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Affiliation(s)
- Wael M Osman
- Center of Biotechnology, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Herbert F Jelinek
- School of Community Health, Charles Sturt University, Albury, New South Wales, Australia
- Clinical Medicine, Macquarie University, Sydney, New South Wales, Australia
| | - Guan K Tay
- Center of Biotechnology, Khalifa University, Abu Dhabi, United Arab Emirates
- School of Health and Medical Sciences, Edith Cowan University, Joondalup, Western Australia, Australia
- School of Psychiatry and Clinical Neurosciences, University of Western Australia, Western Australia, Australia
- Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Ahsan H Khandoker
- Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Kinda Khalaf
- Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Wael Almahmeed
- Institute of Cardiac Science, Sheikh Khalifa Medical City, Abu Dhabi, United Arab Emirates
- Heart and Vascular Institute, Cleveland Clinic, Abu Dhabi, United Arab Emirates
| | - Mohamed H Hassan
- Medical Institute, Sheikh Khalifa Medical City, Abu Dhabi, United Arab Emirates
| | - Habiba S Alsafar
- Center of Biotechnology, Khalifa University, Abu Dhabi, United Arab Emirates
- Biomedical Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
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7
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Murray GGR, Soares AER, Novak BJ, Schaefer NK, Cahill JA, Baker AJ, Demboski JR, Doll A, Da Fonseca RR, Fulton TL, Gilbert MTP, Heintzman PD, Letts B, McIntosh G, O'Connell BL, Peck M, Pipes ML, Rice ES, Santos KM, Sohrweide AG, Vohr SH, Corbett-Detig RB, Green RE, Shapiro B. Natural selection shaped the rise and fall of passenger pigeon genomic diversity. Science 2018; 358:951-954. [PMID: 29146814 DOI: 10.1126/science.aao0960] [Citation(s) in RCA: 70] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 09/28/2017] [Indexed: 12/13/2022]
Abstract
The extinct passenger pigeon was once the most abundant bird in North America, and possibly the world. Although theory predicts that large populations will be more genetically diverse, passenger pigeon genetic diversity was surprisingly low. To investigate this disconnect, we analyzed 41 mitochondrial and 4 nuclear genomes from passenger pigeons and 2 genomes from band-tailed pigeons, which are passenger pigeons' closest living relatives. Passenger pigeons' large population size appears to have allowed for faster adaptive evolution and removal of harmful mutations, driving a huge loss in their neutral genetic diversity. These results demonstrate the effect that selection can have on a vertebrate genome and contradict results that suggested that population instability contributed to this species's surprisingly rapid extinction.
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Affiliation(s)
- Gemma G R Murray
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA
| | - André E R Soares
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA
| | - Ben J Novak
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA.,Revive & Restore, Sausalito, CA 94965, USA
| | - Nathan K Schaefer
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - James A Cahill
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA
| | - Allan J Baker
- Department of Natural History, Royal Ontario Museum, Toronto, ON M5S 2C6, Canada
| | - John R Demboski
- Department of Zoology, Denver Museum of Nature and Science, Denver, CO 80205, USA
| | - Andrew Doll
- Department of Zoology, Denver Museum of Nature and Science, Denver, CO 80205, USA
| | - Rute R Da Fonseca
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark
| | - Tara L Fulton
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA.,Environment and Climate Change Canada, 9250-49th Street, Edmonton, AB T6B 1K5, Canada
| | - M Thomas P Gilbert
- Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, Øster Voldgade 5-7, 1350 Copenhagen, Denmark.,NTNU University Museum, 7491 Trondheim, Norway
| | - Peter D Heintzman
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA.,Tromsø University Museum, UiT-The Arctic University of Norway, 9037 Tromsø, Norway
| | - Brandon Letts
- Department of Biology, The Pennsylvania State University, University Park, PA 16802, USA
| | - George McIntosh
- Collections Department, Rochester Museum and Science Center, Rochester, NY 14607, USA
| | - Brendan L O'Connell
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Mark Peck
- Department of Zoology, Denver Museum of Nature and Science, Denver, CO 80205, USA
| | | | - Edward S Rice
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Kathryn M Santos
- Collections Department, Rochester Museum and Science Center, Rochester, NY 14607, USA
| | | | - Samuel H Vohr
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Russell B Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.,University of California Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA 95064, USA
| | - Richard E Green
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA.,University of California Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA 95064, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, CA 95064, USA. .,University of California Santa Cruz Genomics Institute, 1156 High Street, Santa Cruz, CA 95064, USA
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8
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Prokop JW, Yeo NC, Ottmann C, Chhetri SB, Florus KL, Ross EJ, Sosonkina N, Link BA, Freedman BI, Coppola CJ, McDermott-Roe C, Leysen S, Milroy LG, Meijer FA, Geurts AM, Rauscher FJ, Ramaker R, Flister MJ, Jacob HJ, Mendenhall EM, Lazar J. Characterization of Coding/Noncoding Variants for SHROOM3 in Patients with CKD. J Am Soc Nephrol 2018; 29:1525-1535. [PMID: 29476007 DOI: 10.1681/asn.2017080856] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 01/19/2018] [Indexed: 12/16/2022] Open
Abstract
Background Interpreting genetic variants is one of the greatest challenges impeding analysis of rapidly increasing volumes of genomic data from patients. For example, SHROOM3 is an associated risk gene for CKD, yet causative mechanism(s) of SHROOM3 allele(s) are unknown.Methods We used our analytic pipeline that integrates genetic, computational, biochemical, CRISPR/Cas9 editing, molecular, and physiologic data to characterize coding and noncoding variants to study the human SHROOM3 risk locus for CKD.Results We identified a novel SHROOM3 transcriptional start site, which results in a shorter isoform lacking the PDZ domain and is regulated by a common noncoding sequence variant associated with CKD (rs17319721, allele frequency: 0.35). This variant disrupted allele binding to the transcription factor TCF7L2 in podocyte cell nuclear extracts and altered transcription levels of SHROOM3 in cultured cells, potentially through the loss of repressive looping between rs17319721 and the novel start site. Although common variant mechanisms are of high utility, sequencing is beginning to identify rare variants involved in disease; therefore, we used our biophysical tools to analyze an average of 112,849 individual human genome sequences for rare SHROOM3 missense variants, revealing 35 high-effect variants. The high-effect alleles include a coding variant (P1244L) previously associated with CKD (P=0.01, odds ratio=7.95; 95% CI, 1.53 to 41.46) that we find to be present in East Asian individuals at an allele frequency of 0.0027. We determined that P1244L attenuates the interaction of SHROOM3 with 14-3-3, suggesting alterations to the Hippo pathway, a known mediator of CKD.Conclusions These data demonstrate multiple new SHROOM3-dependent genetic/molecular mechanisms that likely affect CKD.
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Affiliation(s)
- Jeremy W Prokop
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama; .,Department of Pediatrics and Human Development, Michigan State University, Grand Rapids, Michigan
| | - Nan Cher Yeo
- Department of Genetics, Harvard Medical School, Boston, Massachusetts
| | - Christian Ottmann
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, The Netherlands.,Department of Chemistry, University of Duisburg-Essen, Essen, Germany
| | - Surya B Chhetri
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama.,Department of Biological Sciences, The University of Alabama in Huntsville, Huntsville, Alabama
| | - Kacie L Florus
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama
| | - Emily J Ross
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama.,Department of Chemical and Physical Biology, Vanderbilt University, Nashville, Tennessee
| | | | - Brian A Link
- Department of Cell Biology, Neurobiology and Anatomy and
| | - Barry I Freedman
- Section on Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina; and
| | - Candice J Coppola
- Department of Biological Sciences, The University of Alabama in Huntsville, Huntsville, Alabama
| | - Chris McDermott-Roe
- Department of Physiology, Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Seppe Leysen
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Lech-Gustav Milroy
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Femke A Meijer
- Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Aron M Geurts
- Department of Physiology, Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Frank J Rauscher
- Gene Expression & Regulation Program, Wistar Institute, Philadelphia, Pennsylvania
| | - Ryne Ramaker
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama
| | - Michael J Flister
- Department of Physiology, Human and Molecular Genetics Center, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Howard J Jacob
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama
| | - Eric M Mendenhall
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama.,Department of Biological Sciences, The University of Alabama in Huntsville, Huntsville, Alabama
| | - Jozef Lazar
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama;
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Devuyst O, Pattaro C. The UMOD Locus: Insights into the Pathogenesis and Prognosis of Kidney Disease. J Am Soc Nephrol 2017; 29:713-726. [PMID: 29180396 DOI: 10.1681/asn.2017070716] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
The identification of genetic factors associated with kidney disease has the potential to provide critical insights into disease mechanisms. Genome-wide association studies have uncovered genomic regions associated with renal function metrics and risk of CKD. UMOD is among the most outstanding loci associated with CKD in the general population, because it has a large effect on eGFR and CKD risk that is consistent across different ethnic groups. The relevance of UMOD for CKD is clear, because the encoded protein, uromodulin (Tamm-Horsfall protein), is exclusively produced by the kidney tubule and has specific biochemical properties that mediate important functions in the kidney and urine. Rare mutations in UMOD are the major cause of autosomal dominant tubulointerstitial kidney disease, a condition that leads to CKD and ESRD. In this brief review, we use the UMOD paradigm to describe how population genetic studies can yield insight into the pathogenesis and prognosis of kidney diseases.
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Affiliation(s)
- Olivier Devuyst
- Institute of Physiology, University of Zurich, Zurich, Switzerland; and
| | - Cristian Pattaro
- Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy
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10
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Taški-Ajduković K, Nagl N, Ćurčić Ž, Zorić M. Estimation of genetic diversity and relationship in sugar beet pollinators based on SSR markers. ELECTRON J BIOTECHN 2017. [DOI: 10.1016/j.ejbt.2017.02.001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
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11
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Barth S, Jankowska MJ, Hodkinson TR, Vellani T, Klaas M. Variation in sequences containing microsatellite motifs in the perennial biomass and forage grass, Phalaris arundinacea (Poaceae). BMC Res Notes 2016; 9:184. [PMID: 27005474 PMCID: PMC4804619 DOI: 10.1186/s13104-016-1994-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Accepted: 03/16/2016] [Indexed: 12/03/2022] Open
Abstract
Forty three microsatellite markers were developed for further genetic characterisation of a forage and biomass grass crop, for which genomic resources are currently scarce. The microsatellite markers were developed from a normalized EST-SSR library. All of the 43 markers gave a clear banding pattern on 3 % Metaphor agarose gels. Eight selected SSR markers were tested in detail for polymorphism across eleven DNA samples of large geographic distribution across Europe. The new set of 43 SSR markers will help future research to characterise the genetic structure and diversity of Phalaris arundinacea, with a potential to further understand its invasive character in North American wetlands, as well as aid in breeding work for desired biomass and forage traits. P. arundinacea is particularly valued in the northern latitude as a crop with high biomass potential, even more so on marginal lands.
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Affiliation(s)
- Susanne Barth
- Teagasc Crops Environment and Land Use Programme, Oak Park Research Centre, Carlow, Ireland.
| | | | | | - Tia Vellani
- Teagasc Crops Environment and Land Use Programme, Oak Park Research Centre, Carlow, Ireland
| | - Manfred Klaas
- Teagasc Crops Environment and Land Use Programme, Oak Park Research Centre, Carlow, Ireland
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12
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Ghirotto S, Tassi F, Barbujani G, Pattini L, Hayward C, Vollenweider P, Bochud M, Rampoldi L, Devuyst O. The Uromodulin Gene Locus Shows Evidence of Pathogen Adaptation through Human Evolution. J Am Soc Nephrol 2016; 27:2983-2996. [PMID: 26966016 DOI: 10.1681/asn.2015070830] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2015] [Accepted: 01/30/2016] [Indexed: 12/15/2022] Open
Abstract
Common variants in the UMOD gene encoding uromodulin, associated with risk of hypertension and CKD in the general population, increase UMOD expression and urinary excretion of uromodulin, causing salt-sensitive hypertension and renal lesions. To determine the effect of selective pressure on variant frequency, we investigated the allelic frequency of the lead UMOD variant rs4293393 in 156 human populations, in eight ancient human genomes, and in primate genomes. The T allele of rs4293393, associated with CKD risk, has high frequency in most modern populations and was the one detected in primate genomes. In contrast, we identified only the derived, C allele in Denisovan and Neanderthal genomes. The distribution of the UMOD ancestral allele did not follow the ancestral susceptibility model observed for variants associated with salt-sensitive hypertension. Instead, the global frequencies of the UMOD alleles significantly correlated with pathogen diversity (bacteria, helminths) and prevalence of antibiotic-resistant urinary tract infections (UTIs). The inverse correlation found between urinary levels of uromodulin and markers of UTIs in the general population substantiates the link between UMOD variants and protection against UTIs. These data strongly suggest that the UMOD ancestral allele, driving higher urinary excretion of uromodulin, has been kept at a high frequency because of its protective effect against UTIs.
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Affiliation(s)
- Silvia Ghirotto
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Francesca Tassi
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Guido Barbujani
- Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy
| | - Linda Pattini
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy
| | - Caroline Hayward
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Peter Vollenweider
- Department of Internal Medicine, Institute of Social and Preventive Medicine, Lausanne University Hospital Center, Lausanne, Switzerland
| | - Murielle Bochud
- Department of Internal Medicine, Institute of Social and Preventive Medicine, Lausanne University Hospital Center, Lausanne, Switzerland
| | - Luca Rampoldi
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy; and
| | - Olivier Devuyst
- Institute of Physiology, University of Zurich, Zurich, Switzerland
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Sattler MC, Carvalho CR, Clarindo WR. The polyploidy and its key role in plant breeding. PLANTA 2016; 243:281-96. [PMID: 26715561 DOI: 10.1007/s00425-015-2450-x] [Citation(s) in RCA: 211] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2015] [Accepted: 12/16/2015] [Indexed: 05/19/2023]
Abstract
This article provides an up-to-date review concerning from basic issues of polyploidy to aspects regarding the relevance and role of both natural and artificial polyploids in plant breeding programs. Polyploidy is a major force in the evolution of both wild and cultivated plants. Polyploid organisms often exhibit increased vigor and, in some cases, outperform their diploid relatives in several aspects. This remarkable superiority of polyploids has been the target of many plant breeders in the last century, who have induced polyploidy and/or used natural polyploids in many ways to obtain increasingly improved plant cultivars. Some of the most important consequences of polyploidy for plant breeding are the increment in plant organs ("gigas" effect), buffering of deleterious mutations, increased heterozygosity, and heterosis (hybrid vigor). Regarding such features as tools, cultivars have been generated with higher yield levels, improving the product quality and increasing the tolerance to both biotic and abiotic stresses. In some cases, when the crossing between two species is not possible because of differences in ploidy level, polyploids can be used as a bridge for gene transferring between them. In addition, polyploidy often results in reduced fertility due to meiotic errors, allowing the production of seedless varieties. On the other hand, the genome doubling in a newly formed sterile hybrid allows the restoration of its fertility. Based on these aspects, the present review initially concerns the origin, frequency and classification of the polyploids, progressing to show the revolution promoted by the discovery of natural polyploids and polyploidization induction in the breeding program status of distinct crops.
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Affiliation(s)
- Mariana Cansian Sattler
- Laboratório de Citogenética, Departamento de Biologia, Centro de Ciências Agrárias, Universidade Federal do Espírito Santo, Alegre, ES, CEP: 29.500-000, Brazil
| | - Carlos Roberto Carvalho
- Laboratório de Citogenética e Citometria, Departamento de Biologia Geral, Centro de Ciências Biológicas e da Saúde, Universidade Federal de Viçosa, Viçosa, MG, CEP: 36.570-000, Brazil
| | - Wellington Ronildo Clarindo
- Laboratório de Citogenética, Departamento de Biologia, Centro de Ciências Agrárias, Universidade Federal do Espírito Santo, Alegre, ES, CEP: 29.500-000, Brazil.
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Ribeiro IC, Pinheiro C, Ribeiro CM, Veloso MM, Simoes-Costa MC, Evaristo I, Paulo OS, Ricardo CP. Genetic Diversity and Physiological Performance of Portuguese Wild Beet (Beta vulgaris spp. maritima) from Three Contrasting Habitats. FRONTIERS IN PLANT SCIENCE 2016; 7:1293. [PMID: 27630646 PMCID: PMC5006101 DOI: 10.3389/fpls.2016.01293] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/29/2016] [Accepted: 08/12/2016] [Indexed: 05/20/2023]
Abstract
The establishment of stress resilient sugar beets (Beta vulgaris spp. vulgaris) is an important breeding goal since this cash crop is susceptible to drought and salinity. The genetic diversity in cultivated sugar beets is low and the beet wild relatives are useful genetic resources for tolerance traits. Three wild beet populations (Beta vulgaris spp. maritima) from contrasting environments, Vaiamonte (VMT, dry inland hill), Comporta (CMP, marsh) and Oeiras (OEI, coastland), and one commercial sugar beet (Isella variety, SB), are compared. At the genetic level, the use of six microsatellite allowed to detect a total of seventy six alleles. It was observed that CMP population has the highest value concerning the effective number of alleles and of expected heterozygosity. By contrast, sugar beet has the lowest values for all the parameters considered. Loci analysis with STRUCTURE allows defining three genetic clusters, the sea beet (OEI and CMP), the inland ruderal beet (VMT) and the sugar beet (SB). A screening test for progressive drought and salinity effects demonstrated that: all populations were able to recover from severe stress; drought impact was higher than that from salinity; the impact on biomass (total, shoot, root) was population specific. The distinct strategies were also visible at physiological level. We evaluated the physiological responses of the populations under drought and salt stress, namely at initial stress stages, late stress stages, and early stress recovery. Multivariate analysis showed that the physiological performance can be used to discriminate between genotypes, with a strong contribution of leaf temperature and leaf osmotic adjustment. However, the separation achieved and the groups formed are dependent on the stress type, stress intensity and duration. Each of the wild beet populations evaluated is very rich in genetic terms (allelic richness) and exhibited physiological plasticity, i.e., the capacity to physiologically adjust to changing environments. These characteristics emphasize the importance of the wild beet ecotypes for beet improvement programs. Two striking ecotypes are VMT, which is the best to cope with drought and salinity, and CMP which has the highest root to shoot ratio. These genotypes can supply breeding programs with distinct goals.
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Affiliation(s)
- Isa C. Ribeiro
- Instituto de Tecnologia Química e Biológica, Universidade NOVA de LisboaOeiras, Portugal
| | - Carla Pinheiro
- Instituto de Tecnologia Química e Biológica, Universidade NOVA de LisboaOeiras, Portugal
- Faculdade de Ciências e Tecnologia, Universidade NOVA de LisboaCaparica, Portugal
- *Correspondence: Carla Pinheiro,
| | - Carla M. Ribeiro
- Computational Biology and Population Genomics Group, Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências da Universidade de LisboaLisboa, Portugal
| | - Maria M. Veloso
- INIAV, Unidade de Investigação de Biotecnologia e Recursos GenéticosOeiras, Portugal
- Instituto Superior de Agronomia, Linking Landscape, Environment, Agriculture and Food, Universidade de LisboaLisboa, Portugal
| | - Maria C. Simoes-Costa
- Instituto Superior de Agronomia, Linking Landscape, Environment, Agriculture and Food, Universidade de LisboaLisboa, Portugal
| | - Isabel Evaristo
- INIAV, Unidade de Investigação de Sistemas Agrários e Florestais e Sanidade VegetalOeiras, Portugal
| | - Octávio S. Paulo
- Computational Biology and Population Genomics Group, Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências da Universidade de LisboaLisboa, Portugal
| | - Cândido P. Ricardo
- Instituto de Tecnologia Química e Biológica, Universidade NOVA de LisboaOeiras, Portugal
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Iquebal MA, Jaiswal S, Angadi UB, Sablok G, Arora V, Kumar S, Rai A, Kumar D. SBMDb: first whole genome putative microsatellite DNA marker database of sugarbeet for bioenergy and industrial applications. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2015; 2015:bav111. [PMID: 26647370 PMCID: PMC4672366 DOI: 10.1093/database/bav111] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Accepted: 10/24/2015] [Indexed: 11/14/2022]
Abstract
DNA marker plays important role as valuable tools to increase crop productivity by finding plausible answers to genetic variations and linking the Quantitative Trait Loci (QTL) of beneficial trait. Prior approaches in development of Short Tandem Repeats (STR) markers were time consuming and inefficient. Recent methods invoking the development of STR markers using whole genomic or transcriptomics data has gained wide importance with immense potential in developing breeding and cultivator improvement approaches. Availability of whole genome sequences and in silico approaches has revolutionized bulk marker discovery. We report world's first sugarbeet whole genome marker discovery having 145 K markers along with 5 K functional domain markers unified in common platform using MySQL, Apache and PHP in SBMDb. Embedded markers and corresponding location information can be selected for desired chromosome, location/interval and primers can be generated using Primer3 core, integrated at backend. Our analyses revealed abundance of 'mono' repeat (76.82%) over 'di' repeats (13.68%). Highest density (671.05 markers/Mb) was found in chromosome 1 and lowest density (341.27 markers/Mb) in chromosome 6. Current investigation of sugarbeet genome marker density has direct implications in increasing mapping marker density. This will enable present linkage map having marker distance of ∼2 cM, i.e. from 200 to 2.6 Kb, thus facilitating QTL/gene mapping. We also report e-PCR-based detection of 2027 polymorphic markers in panel of five genotypes. These markers can be used for DUS test of variety identification and MAS/GAS in variety improvement program. The present database presents wide source of potential markers for developing and implementing new approaches for molecular breeding required to accelerate industrious use of this crop, especially for sugar, health care products, medicines and color dye. Identified markers will also help in improvement of bioenergy trait of bioethanol and biogas production along with reaping advantage of crop efficiency in terms of low water and carbon footprint especially in era of climate change. Database URL: http://webapp.cabgrid.res.in/sbmdb/.
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Affiliation(s)
- Mir Asif Iquebal
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
| | - Sarika Jaiswal
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
| | - U B Angadi
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
| | - Gaurav Sablok
- Biotechnology Unit, Department of Botany, Jai Narain Vyas University, Jodhpur 342003, India, Plant Functional Biology and Climate Change Cluster (C3), University of Technology, Sydney, PO Box 123 Broadway New South Wales 2007, Australia
| | - Vasu Arora
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
| | - Sunil Kumar
- National Bureau of Agriculturally Important Microorganisms, Kusmaur, Mau NathBhanjan, Uttar Pradesh 275101, India and Institute of Life Sciences, Nalco Square, Bhubaneswar 751023, India
| | - Anil Rai
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India
| | - Dinesh Kumar
- Centre for Agricultural Bioinformatics, Indian Agricultural Statistics Research Institute, Library Avenue, PUSA, New Delhi 110012, India,
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16
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Addisalem AB, Esselink GD, Bongers F, Smulders MJM. Genomic sequencing and microsatellite marker development for Boswellia papyrifera, an economically important but threatened tree native to dry tropical forests. AOB PLANTS 2015; 7:plu086. [PMID: 25573702 PMCID: PMC4433549 DOI: 10.1093/aobpla/plu086] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2014] [Accepted: 12/08/2014] [Indexed: 06/01/2023]
Abstract
Microsatellite (or simple sequence repeat, SSR) markers are highly informative DNA markers often used in conservation genetic research. Next-generation sequencing enables efficient development of large numbers of SSR markers at lower costs. Boswellia papyrifera is an economically important tree species used for frankincense production, an aromatic resinous gum exudate from bark. It grows in dry tropical forests in Africa and is threatened by a lack of rejuvenation. To help guide conservation efforts for this endangered species, we conducted an analysis of its genomic DNA sequences using Illumina paired-end sequencing. The genome size was estimated at 705 Mb per haploid genome. The reads contained one microsatellite repeat per 5.7 kb. Based on a subset of these repeats, we developed 46 polymorphic SSR markers that amplified 2-12 alleles in 10 genotypes. This set included 30 trinucleotide repeat markers, four tetranucleotide repeat markers, six pentanucleotide markers and six hexanucleotide repeat markers. Several markers were cross-transferable to Boswellia pirrotae and B. popoviana. In addition, retrotransposons were identified, the reads were assembled and several contigs were identified with similarity to genes of the terpene and terpenoid backbone synthesis pathways, which form the major constituents of the bark resin.
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Affiliation(s)
- A B Addisalem
- Wageningen UR Plant Breeding, Wageningen University and Research Center, PO Box 386, NL-6700 AJ Wageningen, The Netherlands Center for Ecosystem Studies, Forest Ecology and Forest Management Group, Wageningen University and Research Center, PO Box 47, NL-6700 AA Wageningen, The Netherlands Wondo Genet College of Forestry and Natural Resources, PO Box 128, Shashemene, Ethiopia
| | - G Danny Esselink
- Wageningen UR Plant Breeding, Wageningen University and Research Center, PO Box 386, NL-6700 AJ Wageningen, The Netherlands
| | - F Bongers
- Center for Ecosystem Studies, Forest Ecology and Forest Management Group, Wageningen University and Research Center, PO Box 47, NL-6700 AA Wageningen, The Netherlands
| | - M J M Smulders
- Wageningen UR Plant Breeding, Wageningen University and Research Center, PO Box 386, NL-6700 AJ Wageningen, The Netherlands
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17
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Scolari F, Izzi C, Ghiggeri GM. Uromodulin: from monogenic to multifactorial diseases: FIGURE 1:. Nephrol Dial Transplant 2014; 30:1250-6. [DOI: 10.1093/ndt/gfu300] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Accepted: 08/21/2014] [Indexed: 12/30/2022] Open
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18
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Adetunji I, Willems G, Tschoep H, Bürkholz A, Barnes S, Boer M, Malosetti M, Horemans S, van Eeuwijk F. Genetic diversity and linkage disequilibrium analysis in elite sugar beet breeding lines and wild beet accessions. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2014; 127:559-571. [PMID: 24292512 DOI: 10.1007/s00122-013-2239-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2013] [Accepted: 11/20/2013] [Indexed: 06/02/2023]
Abstract
Linkage disequilibrium decay in sugar beet is strongly affected by the breeding history, and varies extensively between and along chromosomes, allowing identification of known and unknown signatures of selection. Genetic diversity and linkage disequilibrium (LD) patterns were investigated in 233 elite sugar beet breeding lines and 91 wild beet accessions, using 454 single nucleotide polymorphisms (SNPs) and 418 SNPs, respectively. Principal coordinate analysis suggested the existence of three groups of germplasm, corresponding to the wild beets, the seed parent and the pollen parent breeding pool. LD was investigated in each of these groups, with and without correction for genetic relatedness. Without correction for genetic relatedness, in the pollen as well as the seed parent pool, LD persisted beyond 50 centiMorgan (cM) on four (2, 3, 4 and 5) and three chromosomes (2, 4 and 6), respectively; after correction for genetic relatedness, LD decayed after <6 cM on all chromosomes in both pools. In the wild beet accessions, there was a strong LD decay: on average LD disappeared after 1 cM when LD was calculated with a correction for genetic relatedness. Persistence of LD was not only observed between distant SNPs on the same chromosome, but also between SNPs on different chromosomes. Regions on chromosomes 3 and 4 that harbor disease resistance and monogermy loci showed strong genetic differentiation between the pollen and seed parent pools. Other regions, on chromosomes 8 and 9, for which no a priori information was available with respect to their contribution to the phenotype, still contributed to clustering of lines in the elite breeding material.
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19
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Parsa A, Fuchsberger C, Köttgen A, O’Seaghdha CM, Pattaro C, de Andrade M, Chasman DI, Teumer A, Endlich K, Olden M, Chen MH, Tin A, Kim YJ, Taliun D, Li M, Feitosa M, Gorski M, Yang Q, Hundertmark C, Foster MC, Glazer N, Isaacs A, Rao M, Smith AV, O’Connell JR, Struchalin M, Tanaka T, Li G, Hwang SJ, Atkinson EJ, Lohman K, Cornelis MC, Johansson Å, Tönjes A, Dehghan A, Couraki V, Holliday EG, Sorice R, Kutalik Z, Lehtimäki T, Esko T, Deshmukh H, Ulivi S, Chu AY, Murgia F, Trompet S, Imboden M, Kollerits B, Pistis G, Harris TB, Launer LJ, Aspelund T, Eiriksdottir G, Mitchell BD, Boerwinkle E, Schmidt H, Hofer E, Hu F, Demirkan A, Oostra BA, Turner ST, Ding J, Andrews JS, Freedman BI, Giulianini F, Koenig W, Illig T, Döring A, Wichmann HE, Zgaga L, Zemunik T, Boban M, Minelli C, Wheeler HE, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D, Nöthlings U, Jacobs G, Biffar R, Ernst F, Homuth G, Kroemer HK, Nauck M, Stracke S, Völker U, Völzke H, Kovacs P, Stumvoll M, Mägi R, Hofman A, Uitterlinden AG, Rivadeneira F, Aulchenko YS, Polasek O, Hastie N, Vitart V, Helmer C, Wang JJ, Stengel B, Ruggiero D, Bergmann S, Kähönen M, Viikari J, Nikopensius T, Province M, Colhoun H, Doney A, Robino A, Krämer BK, Portas L, Ford I, Buckley BM, Adam M, Thun GA, Paulweber B, Haun M, Sala C, Mitchell P, Ciullo M, Vollenweider P, Raitakari O, Metspalu A, Palmer C, Gasparini P, Pirastu M, Jukema JW, Probst-Hensch NM, Kronenberg F, Toniolo D, Gudnason V, Shuldiner AR, Coresh J, Schmidt R, Ferrucci L, van Duijn CM, Borecki I, Kardia SL, Liu Y, Curhan GC, Rudan I, Gyllensten U, Wilson JF, Franke A, Pramstaller PP, Rettig R, Prokopenko I, Witteman J, Hayward C, Ridker PM, Bochud M, Heid IM, Siscovick DS, Fox CS, Kao WL, Böger CA. Common variants in Mendelian kidney disease genes and their association with renal function. J Am Soc Nephrol 2013; 24:2105-17. [PMID: 24029420 PMCID: PMC3839542 DOI: 10.1681/asn.2012100983] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2012] [Accepted: 07/10/2013] [Indexed: 12/28/2022] Open
Abstract
Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.
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Affiliation(s)
- Afshin Parsa
- Division of Nephrology, University of Maryland School of Medicine, Baltimore, Maryland
| | - Christian Fuchsberger
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Anna Köttgen
- Renal Division, Freiburg University Clinic, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Conall M. O’Seaghdha
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
- Division of Nephrology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Cristian Pattaro
- Centre for Biomedicine, European Academy of Bozen/Bolzano, Bolzano, Italy
| | - Mariza de Andrade
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Alexander Teumer
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Karlhans Endlich
- Institute of Anatomy and Cell Biology, University of Greifswald, Greifswald, Germany
| | - Matthias Olden
- Division of Nephrology, Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Ming-Huei Chen
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Adrienne Tin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Young J. Kim
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
- Genomics Resource Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea
| | - Daniel Taliun
- Centre for Biomedicine, European Academy of Bozen/Bolzano, Bolzano, Italy
| | - Man Li
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Mary Feitosa
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri
| | - Mathias Gorski
- Division of Nephrology, Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University Hospital Regensburg, Regensburg, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | | | - Meredith C. Foster
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
| | - Nicole Glazer
- Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston, Massachusetts
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Centre for Medical Systems Biology, Rotterdam, The Netherlands
| | - Madhumathi Rao
- Division of Nephrology, Tufts Evidence Practice Center, Tufts University School of Medicine, Tufts Medical Center, Boston, Massachusetts
| | - Albert V. Smith
- Research Institute, Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Jeffrey R. O’Connell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Maksim Struchalin
- Departments of Epidemiology and Biostatistics and Forensic Molecular Biology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute of Aging, Baltimore Maryland
| | - Guo Li
- University of Washington, Seattle, Washington
| | - Shih-Jen Hwang
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
| | - Elizabeth J. Atkinson
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota
| | - Kurt Lohman
- Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Marilyn C. Cornelis
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
| | - Åsa Johansson
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Adiposity Diseases Integrated Research and Treatment Center, University of Leipzig, Leipzig, Germany
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Elizabeth G. Holliday
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, University of Newcastle, Newcastle, Australia
- Centre for Information-Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
| | - Rossella Sorice
- Adriano-Buzzati Traverso-CNR Institute of Genetics and Biophysics, Naples, Italy
| | - Zoltan Kutalik
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Terho Lehtimäki
- Fimlab Laboratories, Department of Clinical Chemistry, School of Medicine, University of Tampere, Tampere, Finland
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, Estonian Biocentre, University of Tartu, Tartu, Estonia
| | - Harshal Deshmukh
- Wellcome Trust Centre for Molecular Medicine, Clinical Research Centre, University of Dundee, Ninewells Hospital, Dundee, United Kingdom
| | - Sheila Ulivi
- IRCCS Burlo Garofolo Institute for Maternal and Child Health, University of Trieste, Trieste, Italy
| | - Audrey Y. Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | | | - Stella Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Medea Imboden
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Barbara Kollerits
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Giorgio Pistis
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Tamara B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland
| | - Lenore J. Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland
| | - Thor Aspelund
- Research Institute, Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | | | - Braxton D. Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, Texas
| | - Helena Schmidt
- Austrian Stroke Prevention Study, Department of Neurology, Institute of Molecular Biology and Biochemistry, Medical University of Graz, Graz, Austria
| | - Edith Hofer
- Austrian Stroke Prevention Study, Clinical Division of Neurogeriatrics, Department of Neurology, University Clinic of Neurology, Medical University of Graz, Graz, Austria
| | - Frank Hu
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts
| | - Ayse Demirkan
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ben A. Oostra
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Stephen T. Turner
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota
| | - Jingzhong Ding
- Division of Geriatrics, Department of Internal Medicine, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Jeanette S. Andrews
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Barry I. Freedman
- Division of Nephrology, Department of Internal Medicine, Wake Forest School of Medicine, Wake Forest University, Winston-Salem, North Carolina
| | - Franco Giulianini
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Wolfgang Koenig
- Department of Internal Medicine II, Ulm University Clinic, University of Ulm, Ulm, Germany
| | - Thomas Illig
- Hanover Unified Biobank, Hanover Medical School, Hanover, Germany
- Research Unit of Molecular Epidemiology, German Research Center for Environmental Health, Neuherberg, Germany
| | - Angela Döring
- Institute of Epidemiology I and II, German Research Center for Environmental Health, Neuherberg, Germany
| | - H.-Erich Wichmann
- Institute of Epidemiology I and II, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Informatics, Biometry, and Epidemiology, Ludwig-Maximilians-University, Munich, Germany
- Grosshadern Clinic, Neuherberg, Germany
| | - Lina Zgaga
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Tatijana Zemunik
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Mladen Boban
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Cosetta Minelli
- Centre for Biomedicine, European Academy of Bozen/Bolzano, Bolzano, Italy
| | - Heather E. Wheeler
- Department of Genetics, Stanford University, Stanford, California
- Department of Medicine, University of Chicago, Chicago, Illinois
| | - Wilmar Igl
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Ghazal Zaboli
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Sarah H. Wild
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Alan F. Wright
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Harry Campbell
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | - Ute Nöthlings
- PopGen Biobank, Schleswig-Holstein University Hospital, Kiel, Germany
- Institute for Epidemiology, University of Kiel, Kiel, Germany
- Department of Nutrition and Food Sciences, University of Bonn, Bonn, Germany
| | - Gunnar Jacobs
- PopGen Biobank, Schleswig-Holstein University Hospital, Kiel, Germany
- Institute for Epidemiology, University of Kiel, Kiel, Germany
| | - Reiner Biffar
- Clinic for Prosthodontic Dentistry, Gerostomatology, and Material Science, University of Greifswald, Greifswald, Germany
| | - Florian Ernst
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Heyo K. Kroemer
- Institute of Pharmacology, University of Greifswald, Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University of Greifswald, Greifswald, Germany
| | - Sylvia Stracke
- Clinic for Internal Medicine A, University of Greifswald, Greifswald, Germany
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University of Greifswald, Greifswald, Germany
| | - Peter Kovacs
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Michael Stumvoll
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Adiposity Diseases Integrated Research and Treatment Center, University of Leipzig, Leipzig, Germany
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | | | - Fernando Rivadeneira
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Yurii S. Aulchenko
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Ozren Polasek
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Nick Hastie
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Catherine Helmer
- INSERM U897, Institute of Public Health, Victor Segalen Bordeaux II University, Bordeaux, France
- Victor Segalen Bordeaux II University, Bordeaux, France
| | - Jie Jin Wang
- Centre for Vision Research, Westmead Millennium Institute, Westmead Hospital, University of Sydney, Sydney, Australia
- Centre for Eye Research Australia, University of Melbourne, East Melbourne, Australia
| | - Bénédicte Stengel
- INSERM UMRS 1018, Villejuif, France
- UMRS 1018, University of Paris-Sud, Paris, France
| | - Daniela Ruggiero
- Adriano-Buzzati Traverso-CNR Institute of Genetics and Biophysics, Naples, Italy
| | - Sven Bergmann
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, School of Medicine, University of Tampere, Tampere, Finland
| | - Jorma Viikari
- Department of Medicine, Turku University Hospital, University of Turku, Turku, Finland
| | - Tiit Nikopensius
- Institute of Molecular and Cell Biology, Estonian Biocentre, University of Tartu, Tartu, Estonia
| | - Michael Province
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri
| | - Helen Colhoun
- Wellcome Trust Centre for Molecular Medicine, Clinical Research Centre, University of Dundee, Ninewells Hospital, Dundee, United Kingdom
| | - Alex Doney
- National Health Service Tayside, Wellcome Trust Centre for Molecular Medicine, Clinical Research Centre, Ninewells Hospital, Dundee, United Kingdom
| | - Antonietta Robino
- IRCCS Burlo Garofolo Institute for Maternal and Child Health, University of Trieste, Trieste, Italy
| | - Bernhard K. Krämer
- Fifth Department of Medicine, Mannheim University Medical Centre, Mannheim, Germany
| | - Laura Portas
- CNR Institute of Population Genetics, Sassari, Italy
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, United Kingdom
| | - Brendan M. Buckley
- Department of Pharmacology and Therapeutics, University College Cork, Cork, Ireland
| | - Martin Adam
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Gian-Andri Thun
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Bernhard Paulweber
- First Department of Internal Medicine, Paracelsus Medical University, Salzburg, Austria
| | - Margot Haun
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Paul Mitchell
- Centre for Vision Research, Westmead Millennium Institute, Westmead Hospital, University of Sydney, Sydney, Australia
| | - Marina Ciullo
- Adriano-Buzzati Traverso-CNR Institute of Genetics and Biophysics, Naples, Italy
| | - Peter Vollenweider
- Department of Internal Medicine, Vaudois University Hospital Center, University of Lausanne, Lausanne, Switzerland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, Estonian Biocentre, University of Tartu, Tartu, Estonia
| | - Colin Palmer
- Biomedical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, United Kingdom
| | - Paolo Gasparini
- IRCCS Burlo Garofolo Institute for Maternal and Child Health, University of Trieste, Trieste, Italy
| | - Mario Pirastu
- CNR Institute of Population Genetics, Sassari, Italy
| | - J. Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, the Netherlands
- Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
- Einthoven Laboratory for Experimental Vascular Medicine, Leiden, The Netherlands
- Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands
| | - Nicole M. Probst-Hensch
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Innsbruck Medical University, Innsbruck, Austria
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
- CNR Institute of Molecular Genetics, Pavia, Italy
| | - Vilmundur Gudnason
- Research Institute, Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Alan R. Shuldiner
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland
- Geriatric Research and Education Clinical Center, Veterans Affairs Medical Center, Baltimore, Maryland
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, Maryland
| | - Reinhold Schmidt
- Austrian Stroke Prevention Study, Clinical Division of Neurogeriatrics, Department of Neurology, University Clinic of Neurology, Medical University of Graz, Graz, Austria
| | - Luigi Ferrucci
- Clinical Research Branch, National Institute of Aging, Baltimore Maryland
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Centre for Medical Systems Biology, Rotterdam, The Netherlands
- Netherlands Consortium for Healthy Aging, Netherlands Genomics Initiative, Leiden, the Netherlands
| | - Ingrid Borecki
- Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri
| | - Sharon L.R. Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Gary C. Curhan
- Channing Laboratory, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Igor Rudan
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Ulf Gyllensten
- Rudbeck Laboratory, Department of Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - James F. Wilson
- Center for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, Scotland, United Kingdom
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts University, Kiel, Germany
| | | | - Rainer Rettig
- Institute of Physiology, University of Greifswald, Karlsburg, Germany
| | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, United Kingdom
| | - Jacqueline Witteman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, United Kingdom
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts
- Harvard Medical School, Boston, Massachusetts
| | - Murielle Bochud
- University Institute of Social and Preventive Medicine, Vaudois University Hospital Center, University of Lausanne, Lausanne, Switzerland
| | - Iris M. Heid
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany; and
| | | | - Caroline S. Fox
- National Heart, Lung, and Blood Institute's Framingham Heart Study and the Center for Population Studies, Framingham, Massachusetts
- Division of Endocrinology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - W. Linda Kao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, Maryland
| | - Carsten A. Böger
- Division of Nephrology, Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany
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20
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Monteiro F, Romeiras MM, Batista D, Duarte MC. Biodiversity Assessment of Sugar Beet Species and Its Wild Relatives: Linking Ecological Data with New Genetic Approaches. ACTA ACUST UNITED AC 2013. [DOI: 10.4236/ajps.2013.48a003] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Babaei N, Abdullah NAP, Saleh G, Abdullah TL. Isolation and characterization of microsatellite markers and analysis of genetic variability in Curculigo latifolia Dryand. Mol Biol Rep 2012; 39:9869-77. [PMID: 22752726 PMCID: PMC3459080 DOI: 10.1007/s11033-012-1853-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2012] [Accepted: 06/11/2012] [Indexed: 11/26/2022]
Abstract
Curculin, a sweet protein found in Curculigo latifolia fruit has great potential for the pharmaceutical industry. This protein interestingly has been found to have both sweet taste and taste-modifying capacities comparable with other natural sweeteners. According to our knowledge this is the first reported case on the isolation of microsatellite loci in this genus. Hence, the current development of microsatellite markers for C. latifolia will facilitate future population genetic studies and breeding programs for this valuable plant. In this study 11 microsatellite markers were developed using 3' and 5' ISSR markers. The primers were tested on 27 accessions from all states of Peninsular Malaysia. The number of alleles per locus ranged from three to seven, with allele size ranging from 141 to 306 bp. The observed and expected heterozygosity ranged between 0.00-0.65 and 0.38-0.79, respectively. The polymorphic information content ranged from 0.35 to 0.74 and the Shannon's information index ranged from 0.82 to 1.57. These developed polymorphic microsatellites were used for constructing a dendrogram by unweighted pair group method with arithmetic mean cluster analysis using the Dice's similarity coefficient. Accessions association according to their geographical origin was observed. Based on characteristics of isolated microsatellites for C. latifolia accessions all genotype can be distinguished using these 11 microsatellite markers. These polymorphic markers could also be applied to studies on uniformity determination and somaclonal variation of tissue culture plantlets, varieties identification, genetic diversity, analysis of phylogenetic relationship, genetic linkage maps and quantitative trait loci in C. latifolia.
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Affiliation(s)
- Nahid Babaei
- Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang, Selangor Malaysia
| | | | - Ghizan Saleh
- Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang, Selangor Malaysia
| | - Thohirah Lee Abdullah
- Department of Crop Science, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Serdang, Selangor Malaysia
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22
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Simko I, Eujayl I, van Hintum TJL. Empirical evaluation of DArT, SNP, and SSR marker-systems for genotyping, clustering, and assigning sugar beet hybrid varieties into populations. PLANT SCIENCE : AN INTERNATIONAL JOURNAL OF EXPERIMENTAL PLANT BIOLOGY 2012; 184:54-62. [PMID: 22284710 DOI: 10.1016/j.plantsci.2011.12.009] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2011] [Revised: 12/11/2011] [Accepted: 12/13/2011] [Indexed: 05/20/2023]
Abstract
Dominant and co-dominant molecular markers are routinely used in plant genetic research. In the present study we assessed the success-rate of three marker-systems for estimating genotypic diversity, clustering varieties into populations, and assigning a single variety into the expected population. A set of 54 diploid sugar beet (Beta vulgaris L. ssp. vulgaris) hybrid varieties from five seed companies was genotyped with 702 Diversity Array-Technology (DArT), 34 Single Nucleotide Polymorphisms (SNP), and 30 Simple Sequence Repeats (SSR) markers. Analysis of the population structure revealed three well-defined populations and clustering of varieties that generally correlates with their seed company origin. Two populations each contained varieties from two different seed companies indicating genetic similarity of this material. The third population was comprised only of varieties from a single seed company. Analysis of the SSR and SNP datasets indicates that some of the hybrid varieties likely have a common (or very closely related) parent. Comparison of the three marker-systems revealed substantial differences in the number of loci needed for analyses. Varietal clustering required approximately 1.8-2×more SSR, 3-4.5×more SNP, and 4.8×more DArT markers than were required for detection of genotypic diversity. When marker-systems were compared across different types of analyses per locus success-rate was the highest for the SSR and the lowest for the DArT markers. Generally, about 1.4-3×more SNPs, and 4.9-13.3×more DArTs then SSRs were needed to achieve the 100% success-rate. However, using only DArT markers with a high level of polymorphism decreased the number of DArT loci needed for analyses by 38-61%. Results from the present work provide a premise to selecting the type(s) and number of markers that are needed for genetic diversity analysis of sugar beet hybrid varieties.
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Affiliation(s)
- Ivan Simko
- United States Department of Agriculture, Agricultural Research Service, U.S. Agricultural Research Station, 1636 E. Alisal St., Salinas, CA 93905, USA.
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23
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Cieslarová J, Hanáček P, Fialová E, Hýbl M, Smýkal P. Estimation of pea (Pisum sativum L.) microsatellite mutation rate based on pedigree and single-seed descent analyses. J Appl Genet 2011; 52:391-401. [PMID: 21769669 DOI: 10.1007/s13353-011-0058-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2011] [Revised: 06/21/2011] [Accepted: 06/22/2011] [Indexed: 02/07/2023]
Abstract
Microsatellites, or simple sequence repeats (SSRs) are widespread class of repetitive DNA sequences, used in population genetics, genetic diversity and mapping studies. In spite of the SSR utility, the genetic and evolutionary mechanisms are not fully understood. We have investigated three microsatellite loci with different position in the pea (Pisum sativum L.) genome, the A9 locus residing in LTR region of abundant retrotransposon, AD270 as intergenic and AF016458 located in 5'untranslated region of expressed gene. Comparative analysis of a 35 pair samples from seven pea varieties propagated by single-seed descent for ten generations, revealed single 4 bp mutation in 10th generation sample at AD270 locus corresponding to stepwise increase in one additional ATCT repeat unit. The estimated mutation rate was 4.76 × 10(-3) per locus per generation, with a 95% confidence interval of 1.2 × 10(-4) to 2.7 × 10(-2). The comparison of cv. Bohatýr accessions retrieved from different collections, showed intra-, inter-accession variation and differences in flanking and repeat sequences. Fragment size and sequence alternations were also found in long term in vitro organogenic culture, established at 1983, indicative of somatic mutation process. The evidence of homoplasy was detected across of unrelated pea genotypes, which adversaly affects the reliability of diversity estimates not only for diverse germplasm but also highly bred material. The findings of this study have important implications for Pisum phylogeny studies, variety identification and registration process in pea breeding where mutation rate influences the genetic diversity and the effective population size estimates.
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Affiliation(s)
- Jaroslava Cieslarová
- Department of Plant Biology, Mendel University, Zemědělská, Brno, Czech Republic
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