Developing Growth‐Associated Molecular Markers Via High‐Throughput Phenotyping in Spinach

Awika, Henry O.; Bedre, Renesh; Yeom, Junho; Marconi, Thiago G.; Enciso, Juan; Mandadi, Kranthi K.; Jung, Jinha; Avila, Carlos A.

doi:10.3835/plantgenome2019.03.0027

Cited by 17 publications

(22 citation statements)

References 102 publications

(115 reference statements)

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“…Plant material was previously described by Shi, Mou, Correll, Koike, et al (); Shi et al (); Awika et al (). Briefly, the 276 spinach ( Spinacia oleracea L.) accessions used consisted of a diverse panel originating from 33 countries that is part of a diversity collection maintained and provided by the USDA‐National Plant Germplasm System (NPGS) at Ames, Iowa, USA.…”

Section: Methodsmentioning

confidence: 99%

“…Genotyping and SNP calling were performed as described by Awika et al (). Briefly, the 276 spinach accessions were genotyped by sequencing using ddRADseq methodology (Peterson, Weber, Kay, Fisher, & Hoekstra, ).…”

Section: Methodsmentioning

confidence: 99%

“…The 6,167 resulting biallelic SNPs in VCF v4.2 (Danecek et al, ) were used for downstream analyses. SNP by spinach accession data can be downloaded from the Table S1 reported in Awika et al, .…”

Section: Methodsmentioning

confidence: 99%

“…Manhattan and QQ plots were made using the R statistical package, qqman (Turner, ). The genotypic data for the haplotype tags can be found in Table S2 for htP and Table S3 for htM; the genotypic information for the single SNPs (sSNPs) can be downloaded from a previous report (Awika et al, ).…”

Section: Methodsmentioning

confidence: 99%

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Single‐marker and haplotype‐based association analysis of anthracnose (Colletotrichum dematium)resistance in spinach (Spinacia oleracea)

Awika

Cochran²,

Joshi³

et al. 2019

Plant Breeding

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Anthracnose (Colletotrichum dematium) is an important disease in spinach (Spinacia oleracea). Sources of resistance must be identified, and molecular tools must be developed to expedite cultivar development. In this study, a diverse collection of 276 spinach accessions was scored for anthracnose disease severity. We then evaluated marker identification approaches by testing how well haplotype‐based trait modelling compares to single markers in identifying strong association signals. Alleles in linkage disequilibrium were tagged in haplotype blocks, and anthracnose‐associated molecular markers were identified using single‐SNP (sSNP), pairwise haplotype (htP) and multi‐marker haplotype (htM) SNP tagging approaches. We identified 49 significantly associated markers distributed on several spinach chromosomes using all methods. The sSNP approach identified 13 markers, while htP identified 24 (~63% more) and htM 34 (~162% more). Of these markers, four were uniquely identified by the sSNP approach, nine by htP and nineteen by htM. The results indicate that resistance to anthracnose is polygenic and that haplotype‐based analysis may have more power than sSNP. Using a combination of these methods can improve the identification of molecular markers for spinach breeding.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Single‐marker and haplotype‐based association analysis of anthracnose (Colletotrichum dematium)resistance in spinach (Spinacia oleracea)

Awika

Cochran²,

Joshi³

et al. 2019

Plant Breeding

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“…HTS largely replaced conventional low-throughput Sanger-based sequencing technologies for genome-scale studies. Multiple genome sequencing approaches (DNA-seq, RAD-seq, GBS, AgSeq) are being used to study genetic variations, discovery of novel genes, high-throughput genotyping, biomarker discovery, and precision medicine (Awika, et al, 2019;Bolger, et al, 2014;Edwards and Batley, 2010;Kandel, et al, 2019;Suwinski, et al, 2019). Similarly, transcriptome-level sequencing approaches (RNA-seq) allows determining the steadystate expression of genes, identification of novel transcripts and isoforms, alternatively splicing patterns, polymorphisms, gene co-expression networks, allele-specific expressions, and long non-coding RNAs (lincRNA) Xu, et al, 2018;Zhou, et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

HTSQualC is a Flexible and One-Step Quality Control Software for High-throughput Sequencing Data Analysis

Bedre

Avila

Mandadi

2020

Preprint

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MotivationUse of high-throughput sequencing (HTS) has become indispensable in life science research. Raw HTS data contains several sequencing artifacts, and as a first step it is imperative to remove the artifacts for reliable downstream bioinformatics analysis. Although there are multiple stand-alone tools available that can perform the various quality control steps separately, availability of an integrated tool that can allow one-step, automated quality control analysis of HTS datasets will significantly enhance handling large number of samples parallelly.ResultsHere, we developed HTSeqQC, a stand-alone, flexible, and easy-to-use software for one-step quality control analysis of raw HTS data. HTSeqQC can evaluate HTS data quality and perform filtering and trimming analysis in a single run. We evaluated the performance of HTSeqQC for conducting batch analysis of HTS datasets with 322 sample datasets with an average ∼ 1M (paired end) sequence reads per sample. HTSeqQC accomplished the QC analysis in ∼3 hours in distributed mode and ∼31 hours in shared mode, thus underscoring its utility and robust performance.Availability and implementationHTSeqQC software, Docker image and Nextflow template are available for download at https://github.com/reneshbedre/HTSeqQC and graphical user interface (GUI) is available at CyVerse Discovery Environment (DE) (https://cyverse.org/). Documentation available at https://reneshbedre.github.io/blog/htseqqc.html and https://cyverse-htseqqc-cyverse-tutorial.readthedocs-hosted.com/en/latest/ (for CyVerse).ContactKranthi Mandadi (kkmandadi@tamu.edu)Supplementary informationSupplementary information provided in Supplementary File 1.

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An anchored chromosome‐scale genome assembly of spinach improves annotation and reveals extensive gene rearrangements in euasterids

et al. 2021

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Spinach (Spinacia oleracea L.) is a member of the Caryophyllales family, a basal eudicot asterid that consists of sugar beet (Beta vulgaris L. subsp. vulgaris), quinoa (Chenopodium quinoa Willd.), and amaranth (Amaranthus hypochondriacus L.). With the introduction of baby leaf types, spinach has become a staple food in many homes. Production issues focus on yield, nitrogen-use efficiency and resistance to downy mildew (Peronospora effusa). Although genomes are available for the above species, a chromosome-level assembly exists only for quinoa, allowing for proper annotation and structural analyses to enhance crop improvement. We independently

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Developing Growth‐Associated Molecular Markers Via High‐Throughput Phenotyping in Spinach

Abstract: The Plant Genome S pinach, a member of the Amaranthaceae family, is an economically important leafy green crop that is widely grown in the United States. Although the spinach production area has grown steadily during the past 7 yr (

Cited by 17 publications

References 102 publications

Single‐marker and haplotype‐based association analysis of anthracnose (Colletotrichum dematium)resistance in spinach (Spinacia oleracea)

Single‐marker and haplotype‐based association analysis of anthracnose (Colletotrichum dematium)resistance in spinach (Spinacia oleracea)

HTSQualC is a Flexible and One-Step Quality Control Software for High-throughput Sequencing Data Analysis

An anchored chromosome‐scale genome assembly of spinach improves annotation and reveals extensive gene rearrangements in euasterids

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