Evidence map›Paper›PMID 32489396›Full record

ArticlePlant methods2020

All-in-one sequencing: an improved library preparation method for cost-effective and high-throughput next-generation sequencing.

Sheng Zhao, Cuicui Zhang, Jianqiang Mu, Hui Zhang, Wen Yao, Xinhua Ding, Junqiang Ding, Yuxiao Chang

Open access · goldAbstract read
In one paragraph

Article in Plant methods, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.8field-weighted citation impact, top 31% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 16 citations in OpenAlex.

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  12. Whole-exome sequencing identification of a recurrentExperimental and therapeutic medicine · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 5 institutions in 1 country.

Sheng Zhao *Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China.
Cuicui Zhang *College of Life Science and Technology, Guangxi University, Nanning, 530004 China.
Jianqiang MuShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China.
Hui ZhangShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China.
Wen YaoNational Key Laboratory of Wheat and Maize Crop Science, College of Life Sciences, Henan Agricultural University, Zhengzhou, 450002 China.
Xinhua DingState Key Laboratory of Crop Biology, College of Plant Protection, Shandong Agricultural University, Taian, 271018 China.
Junqiang DingNational Key Laboratory of Wheat and Maize Crop Science, College of Agronomy, Henan Agricultural University, Zhengzhou, 450002 China.
Yuxiao ChangShenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518120 China.ORCID 0000-0002-0703-3732
Agricultural Genomics Institute at Shenzhen · CNGuangxi University · CNHenan Agricultural University · CNNational Engineering Research Center for Wheat · CNShandong Agricultural University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNext generation sequencing (NGS) has been widely used in biological research, due to its rapid decrease in cost and increasing ability to generate data. However, while the sequence generation step has seen many improvements over time, the library preparation step has not, resulting in low-efficiency library preparation methods, especially for the most time-consuming and labor-intensive steps: size-selection and quantification. Consequently, there can be bottlenecks in projects with large sample cohorts.

resultsWe have described the all-in-one sequencing (AIO-seq) method, where instead of performing size-selection and quantification for samples individually, one sample one tube, up to 116 samples are pooled and analyzed in a single tube, 'All-In-One'. The AIO-seq method pools libraries based on the samples' expected data yields and the calculated concentrations of the size selected regions (target region), which can easily be obtained with the Agilent 2100 Bioanalyzer and Qubit Fluorometer. AIO-seq was applied to whole genome sequencing and RNA-seq libraries successfully, and it is envisaged that it could be applied to any type of NGS library, such as chromatin immunoprecipitation coupled with massively parallel sequencing, assays for transposase-accessible chromatin with high-throughput sequencing, and high-throughput chromosome conformation capture. We also demonstrated that for genetic population samples with low coverage sequences, like recombinant inbred lines (RIL), AIO-seq could be further simplified, by mixing the libraries immediately after PCR, without calculating the target region concentrations.

conclusionsThe AIO-seq method is thus labor saving and cost effective, and suitable for projects with large sample cohorts, like those used in plant breeding or population genetics research.

Indexed as

All-in-one sequencing (AIO-seq)Library preparationPopulation genetic researchRNA-seqWhole genome sequencing

Identifiers

PMID32489396
PMCPMC7247233
OpenAlexW3032861947

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.