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Brennan C, Salido RA, Belda-Ferre P, Bryant M, Cowart C, Tiu MD, González A, McDonald D, Tribelhorn C, Zarrinpar A, Knight R. Maximizing the potential of high-throughput next-generation sequencing through precise normalization based on read count distribution. mSystems 2023; 8:e0000623. [PMID: 37350611 PMCID: PMC10469589 DOI: 10.1128/msystems.00006-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 04/24/2023] [Indexed: 06/24/2023] Open
Abstract
Next-generation sequencing technologies have enabled many advances across diverse areas of biology, with many benefiting from increased sample size. Although the cost of running next-generation sequencing instruments has dropped substantially over time, the cost of sample preparation methods has lagged behind. To counter this, researchers have adapted library miniaturization protocols and large sample pools to maximize the number of samples that can be prepared by a certain amount of reagents and sequenced in a single run. However, due to high variability of sample quality, over and underrepresentation of samples in a sequencing run has become a major issue in high-throughput sequencing. This leads to misinterpretation of results due to increased noise, and additional time and cost rerunning underrepresented samples. To overcome this problem, we present a normalization method that uses shallow iSeq sequencing to accurately inform pooling volumes based on read distribution. This method is superior to the widely used fluorometry methods, which cannot specifically target adapter-ligated molecules that contribute to sequencing output. Our normalization method not only quantifies adapter-ligated molecules but also allows normalization of feature space; for example, we can normalize to reads of interest such as non-ribosomal reads. As a result, this normalization method improves the efficiency of high-throughput next-generation sequencing by reducing noise and producing higher average reads per sample with more even sequencing depth. IMPORTANCE High-throughput next generation sequencing (NGS) has significantly contributed to the field of genomics; however, further improvements can maximize the potential of this important tool. Uneven sequencing of samples in a multiplexed run is a common issue that leads to unexpected extra costs or low-quality data. To mitigate this problem, we introduce a normalization method based on read counts rather than library concentration. This method allows for an even distribution of features of interest across samples, improving the statistical power of data sets and preventing the financial loss associated with resequencing libraries. This method optimizes NGS, which already has huge importance across many areas of biology.
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Affiliation(s)
- Caitriona Brennan
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Rodolfo A. Salido
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Pedro Belda-Ferre
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - MacKenzie Bryant
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Charles Cowart
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Maria D. Tiu
- Division of Gastroenterology, University of California San Diego, La Jolla, California, USA
| | - Antonio González
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Caitlin Tribelhorn
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - Amir Zarrinpar
- Division of Gastroenterology, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
- VA San Diego Health Sciences, La Jolla, California, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
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Kuplicki R, Touthang J, Al Zoubi O, Mayeli A, Misaki M, Aupperle RL, Teague TK, McKinney BA, Paulus MP, Bodurka J. Common Data Elements, Scalable Data Management Infrastructure, and Analytics Workflows for Large-Scale Neuroimaging Studies. Front Psychiatry 2021; 12:682495. [PMID: 34220587 PMCID: PMC8247461 DOI: 10.3389/fpsyt.2021.682495] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Accepted: 05/19/2021] [Indexed: 01/16/2023] Open
Abstract
Neuroscience studies require considerable bioinformatic support and expertise. Numerous high-dimensional and multimodal datasets must be preprocessed and integrated to create robust and reproducible analysis pipelines. We describe a common data elements and scalable data management infrastructure that allows multiple analytics workflows to facilitate preprocessing, analysis and sharing of large-scale multi-level data. The process uses the Brain Imaging Data Structure (BIDS) format and supports MRI, fMRI, EEG, clinical, and laboratory data. The infrastructure provides support for other datasets such as Fitbit and flexibility for developers to customize the integration of new types of data. Exemplar results from 200+ participants and 11 different pipelines demonstrate the utility of the infrastructure.
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Affiliation(s)
- Rayus Kuplicki
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - James Touthang
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Obada Al Zoubi
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Ahmad Mayeli
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - Masaya Misaki
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - NeuroMAP-Investigators
- Laureate Institute for Brain Research, Tulsa, OK, United States
- Department of Community Medicine, Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, United States
| | - Robin L. Aupperle
- Laureate Institute for Brain Research, Tulsa, OK, United States
- Department of Community Medicine, Oxley College of Health Sciences, University of Tulsa, Tulsa, OK, United States
| | - T. Kent Teague
- Department of Surgery, University of Oklahoma School of Community Medicine, Tulsa, OK, United States
- Department of Psychiatry, University of Oklahoma School of Community Medicine, Tulsa, OK, United States
- Department of Biochemistry and Microbiology, Oklahoma State University Center for Health Sciences, Tulsa, OK, United States
| | - Brett A. McKinney
- Department of Mathematics, University of Tulsa, Tulsa, OK, United States
- Tandy School of Computer Science, University of Tulsa, Tulsa, OK, United States
| | | | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, OK, United States
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
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Ma X, Su Z, Ma H. Molecular genetic analyses of abiotic stress responses during plant reproductive development. J Exp Bot 2020; 71:2870-2885. [PMID: 32072177 PMCID: PMC7260722 DOI: 10.1093/jxb/eraa089] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2019] [Accepted: 02/12/2020] [Indexed: 05/20/2023]
Abstract
Plant responses to abiotic stresses during vegetative growth have been extensively studied for many years. Daily environmental fluctuations can have dramatic effects on plant vegetative growth at multiple levels, resulting in molecular, cellular, physiological, and morphological changes. Plants are even more sensitive to environmental changes during reproductive stages. However, much less is known about how plants respond to abiotic stresses during reproduction. Fortunately, recent advances in this field have begun to provide clues about these important processes, which promise further understanding and a potential contribution to maximize crop yield under adverse environments. Here we summarize information from several plants, focusing on the possible mechanisms that plants use to cope with different types of abiotic stresses during reproductive development, and present a tentative molecular portrait of plant acclimation during reproductive stages. Additionally, we discuss strategies that plants use to balance between survival and productivity, with some comparison among different plants that have adapted to distinct environments.
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Affiliation(s)
- Xinwei Ma
- Department of Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
| | - Zhao Su
- Department of Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
- Correspondence:
| | - Hong Ma
- Department of Biology and the Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
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Frey BM, Petersen M, Mayer C, Schulz M, Cheng B, Thomalla G. Characterization of White Matter Hyperintensities in Large-Scale MRI-Studies. Front Neurol 2019; 10:238. [PMID: 30972001 PMCID: PMC6443932 DOI: 10.3389/fneur.2019.00238] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Accepted: 02/22/2019] [Indexed: 01/18/2023] Open
Abstract
Background: White matter hyperintensities of presumed vascular origin (WMH) are a common finding in elderly people and a growing social malady in the aging western societies. As a manifestation of cerebral small vessel disease, WMH are considered to be a vascular contributor to various sequelae such as cognitive decline, dementia, depression, stroke as well as gait and balance problems. While pathophysiology and therapeutical options remain unclear, large-scale studies have improved the understanding of WMH, particularly by quantitative assessment of WMH. In this review, we aimed to provide an overview of the characteristics, research subjects and segmentation techniques of these studies. Methods: We performed a systematic review according to the PRISMA statement. One thousand one hundred and ninety-six potentially relevant articles were identified via PubMed search. Six further articles classified as relevant were added manually. After applying a catalog of exclusion criteria, remaining articles were read full-text and the following information was extracted into a standardized form: year of publication, sample size, mean age of subjects in the study, the cohort included, and segmentation details like the definition of WMH, the segmentation method, reference to methods papers as well as validation measurements. Results: Our search resulted in the inclusion and full-text review of 137 articles. One hundred and thirty-four of them belonged to 37 prospective cohort studies. Median sample size was 1,030 with no increase over the covered years. Eighty studies investigated in the association of WMH and risk factors. Most of them focussed on arterial hypertension, diabetes mellitus type II and Apo E genotype and inflammatory markers. Sixty-three studies analyzed the association of WMH and secondary conditions like cognitive decline, mood disorder and brain atrophy. Studies applied various methods based on manual (3), semi-automated (57), and automated segmentation techniques (75). Only 18% of the articles referred to an explicit definition of WMH. Discussion: The review yielded a large number of studies engaged in WMH research. A remarkable variety of segmentation techniques was applied, and only a minority referred to a clear definition of WMH. Most addressed topics were risk factors and secondary clinical conditions. In conclusion, WMH research is a vivid field with a need for further standardization regarding definitions and used methods.
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Affiliation(s)
- Benedikt M Frey
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Marvin Petersen
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Carola Mayer
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maximilian Schulz
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bastian Cheng
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Götz Thomalla
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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Pinasseau L, Vallverdú-Queralt A, Verbaere A, Roques M, Meudec E, Le Cunff L, Péros JP, Ageorges A, Sommerer N, Boulet JC, Terrier N, Cheynier V. Cultivar Diversity of Grape Skin Polyphenol Composition and Changes in Response to Drought Investigated by LC-MS Based Metabolomics. Front Plant Sci 2017; 8:1826. [PMID: 29163566 PMCID: PMC5663694 DOI: 10.3389/fpls.2017.01826] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Accepted: 10/10/2017] [Indexed: 05/21/2023]
Abstract
Phenolic compounds represent a large family of plant secondary metabolites, essential for the quality of grape and wine and playing a major role in plant defense against biotic and abiotic stresses. Phenolic composition is genetically driven and greatly affected by environmental factors, including water stress. A major challenge for breeding of grapevine cultivars adapted to climate change and with high potential for wine-making is to dissect the complex plant metabolic response involved in adaptation mechanisms. A targeted metabolomics approach based on ultra high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS) analysis in the Multiple Reaction Monitoring (MRM) mode has been developed for high throughput profiling of the phenolic composition of grape skins. This method enables rapid, selective, and sensitive quantification of 96 phenolic compounds (anthocyanins, phenolic acids, stilbenoids, flavonols, dihydroflavonols, flavan-3-ol monomers, and oligomers…), and of the constitutive units of proanthocyanidins (i.e., condensed tannins), giving access to detailed polyphenol composition. It was applied on the skins of mature grape berries from a core-collection of 279 Vitis vinifera cultivars grown with or without watering to assess the genetic variation for polyphenol composition and its modulation by irrigation, in two successive vintages (2014-2015). Distribution of berry weights and δ13C values showed that non irrigated vines were subjected to a marked water stress in 2014 and to a very limited one in 2015. Metabolomics analysis of the polyphenol composition and chemometrics analysis of this data demonstrated an influence of water stress on the biosynthesis of different polyphenol classes and cultivar differences in metabolic response to water deficit. Correlation networks gave insight on the relationships between the different polyphenol metabolites and related biosynthetic pathways. They also established patterns of polyphenol response to drought, with different molecular families affected either positively or negatively in the different cultivars, with potential impact on grape and wine quality.
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Affiliation(s)
- Lucie Pinasseau
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Anna Vallverdú-Queralt
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Arnaud Verbaere
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Maryline Roques
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
- SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
- IFV Pôle national matériel végétal, UMT Génovigne, Montpellier, France
| | - Emmanuelle Meudec
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Loïc Le Cunff
- IFV Pôle national matériel végétal, UMT Génovigne, Montpellier, France
| | - Jean-Pierre Péros
- AGAP, INRA, CIRAD, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Agnès Ageorges
- SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Nicolas Sommerer
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Jean-Claude Boulet
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Nancy Terrier
- SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
| | - Véronique Cheynier
- Plateforme Polyphénols SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
- SPO, INRA, Montpellier SupAgro, Université de Montpellier, Montpellier, France
- *Correspondence: Véronique Cheynier
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