Applications of genotyping-by-sequencing (GBS) in maize genetics and breeding

Abstract Genotyping-by-Sequencing (GBS) is a low-cost, high-throughput genotyping method that relies on restriction enzymes to reduce genome complexity. GBS is being widely used for various genetic and breeding applications. In the present study, 2240 individuals from eight maize populations, including two association populations (AM), backcross first generation (BC1), BC1F2, F2, double haploid (DH), intermated B73 × Mo17 (IBM), and a recombinant inbred line (RIL) population, were genotyped using GBS. A total of 955,120 of raw data for SNPs was obtained for each individual, with an average genotyping error of 0.70%. The rate of missing genotypic data for these SNPs was related to the level of multiplex sequencing: ~ 25% missing data for 96-plex and ~ 55% for 384-plex. Imputation can greatly reduce the rate of missing genotypes to 12.65% and 3.72% for AM populations and bi-parental populations, respectively, although it increases total genotyping error. For analysis of genetic diversity and linkage mapping, unimputed data with a low rate of genotyping error is beneficial, whereas, for association mapping, imputed data would result in higher marker density and would improve map resolution. Because imputation does not influence the prediction accuracy, both unimputed and imputed data can be used for genomic prediction. In summary, GBS is a versatile and efficient SNP discovery approach for homozygous materials and can be effectively applied for various purposes in maize genetics and breeding.

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Fine-tuning the performance of ddRAD-seq in the peach genome

Scientific Reports ◽

10.1038/s41598-021-85815-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Maximiliano Martín Aballay ◽

Natalia Cristina Aguirre ◽

Carla Valeria Filippi ◽

Gabriel Hugo Valentini ◽

Gerardo Sánchez

Keyword(s):

Germplasm Collection ◽

In Silico Analysis ◽

Genotyping By Sequencing ◽

Fine Tuning ◽

The Novel ◽

Peach Genome ◽

Genome Complexity ◽

Next Generation Sequencing Ngs ◽

Sample Set ◽

Silico Analysis

AbstractThe advance of Next Generation Sequencing (NGS) technologies allows high-throughput genotyping at a reasonable cost, although, in the case of peach, this technology has been scarcely developed. To date, only a standard Genotyping by Sequencing approach (GBS), based on a single restriction with ApeKI to reduce genome complexity, has been applied in peach. In this work, we assessed the performance of the double-digest RADseq approach (ddRADseq), by testing 6 double restrictions with the restriction profile generated with ApeKI. The enzyme pair PstI/MboI retained the highest number of loci in concordance with the in silico analysis. Under this condition, the analysis of a diverse germplasm collection (191 peach genotypes) yielded 200,759,000 paired-end (2 × 250 bp) reads that allowed the identification of 113,411 SNP, 13,661 InDel and 2133 SSR. We take advantage of a wide sample set to describe technical scope of the platform. The novel platform presented here represents a useful tool for genomic-based breeding for peach.

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MICROORGANISMS AS INDICATORS OF SOIL QUALITY

Bulletin Biomedicine and sociology ◽

10.26787/nydha-2618-8783-2021-6-2-45-50 ◽

2021 ◽

pp. 45-50

Author(s):

Kosumov R.S. ◽

Okazova Z.P.

Keyword(s):

Environmental Monitoring ◽

First Generation ◽

Low Cost ◽

Toxicity Tests ◽

Monitoring Methods ◽

Unicellular Algae ◽

Integrated Devices ◽

Eukaryotic Organisms ◽

Biological Methods ◽

State Of The Environment

The first bioassays for environmental monitoring were based on multicellular eukaryotic organisms, in particular fish and mammals. Because they were relatively expensive, time consuming and difficult, there was a need for alternative biological monitoring methods. It became necessary to develop and standardize toxicity tests based on prokaryotic (bacteria) or eukaryotic (protozoa, unicellular algae, yeast) microorganisms instead of higher organisms, which made it possible to quickly and inexpensively screen environmental samples for toxic and genotoxic effects. The first generation of bioassays was based on a variety of naturally sensitive microbes, while the second generation includes genetically modified microorganisms to achieve greater sensitivity and / or specificity. The next step forward was the combination of microbial cells, or parts of cells, with physicochemical detection elements, forming new integrated devices called "biosensors". The purpose of the research is to study the possibility of using microorganisms in bioindication of environmental pollution. The use of biological methods in environmental monitoring is essential to complement chemical analyzes with information on actual toxicity. Microorganisms are widely used as test objects for analyzes due to the simplicity and low cost of their cultivation. The use of microorganisms for the assessment of general toxicity or the detection of specific compounds is an important source of information on the state of the environment. Their use will significantly expand the range of environmental studies.

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Tensile Properties of a Low-Cost First Generation Single Crystal Superalloy DD16

Materials Science Forum ◽

10.4028/www.scientific.net/msf.747-748.478 ◽

2013 ◽

Vol 747-748 ◽

pp. 478-482 ◽

Cited By ~ 5

Author(s):

Jian Wei Xu ◽

Yun Song Zhao ◽

Ding Zhong Tang

Keyword(s):

Tensile Strength ◽

Yield Strength ◽

Single Crystal ◽

Tensile Properties ◽

Cleavage Fracture ◽

Room Temperature ◽

First Generation ◽

Low Cost ◽

Single Crystal Superalloy ◽

Fracture Characteristics

The tensile properties of a low-cost first generation single crystal superalloy DD16 have been investigated. The results show that values of the tensile strength and yield strength of DD16 alloy were similar at typical temperatures; from room temperature to 760, the yield strength of DD16 alloy increases; However, above 760, the yield strength of DD16 alloy decreases remarkably, and the maximum of the yield strength was 1145.5MPa at 760. From room temperature to 760, the fracture mode was cleavage fracture; But above 760, the fracture characteristics changed from cleavage to dimple.

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Fast-GBS v2.0: an analysis toolkit for genotyping-by-sequencing data

Genome ◽

10.1139/gen-2020-0077 ◽

2020 ◽

Vol 63 (11) ◽

pp. 577-581

Author(s):

Davoud Torkamaneh ◽

Jérôme Laroche ◽

François Belzile

Keyword(s):

Data Analysis ◽

Missing Data ◽

Low Cost ◽

Genotyping By Sequencing ◽

Data Imputation ◽

Sequencing Data ◽

Missing Data Imputation ◽

Analysis Process ◽

Computational Resources ◽

Analysis Platform

Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support. Here, we present the second generation of Fast-GBS (v2.0) that offers several new options (e.g., processing paired-end reads and imputation of missing data) and features (e.g., summary statistics of genotypes) to improve the GBS data analysis process. The performance assessment analysis showed that Fast-GBS v2.0 outperformed other available analytical pipelines, such as GBS-SNP-CROP and Gb-eaSy. Fast-GBS v2.0 provides an analysis platform that can be run with different types of sequencing data, modest computational resources, and allows for missing-data imputation for various species in different contexts.

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Breeding Low Emitting Ruminants: Predicting Methane from Microbes

Proceedings ◽

10.3390/proceedings2019036177 ◽

2020 ◽

Vol 36 (1) ◽

pp. 177

Author(s):

Suzanne J. Rowe ◽

Melanie Hess ◽

Larissa Zetouni ◽

Sharon Hickey ◽

Rudiger Brauning ◽

...

Keyword(s):

Energy Source ◽

Low Cost ◽

Genotyping By Sequencing ◽

Methane Emissions ◽

Mitigation Strategies ◽

Microbial Fermentation ◽

Global Access ◽

Research Alliance ◽

Microbial Dna ◽

Ruminant Livestock

The greatest source of global anthropogenic methane (CH4) emissions is from ruminant livestock. Multiple mitigation strategies in livestock are currently being explored. Of these breeding for lower CH4 emitting ruminants has the advantage of being permanent and cumulative and universally applicable to all classes of livestock. Here, we show that methane emissions can be predicted by the complex community of microbiota sampled from rumens enabling evaluation of systems and individuals. Furthermore, there is evidence that the microbial community is controlled not only be the feed substrate but also by the host itself and that selecting hosts that favour a microbial fermentation with lowered methane emissions changes the energy source to the animal, and in turn both rumen physiology and body composition. Current methods for obtaining microbial DNA and subsequent sequencing of an animal’s microbiome, however, are too expensive to implement in commercial selection programs. A methodology that offers fast, low-cost, high throughput profiling of rumen microbiomes using Genotyping-by-sequencing (GBS) has been developed using an unbiased reference free approach to group microbiota. To date, this has been applied to over 4000 sheep samples and validated in cattle. Results show that microbial profiles are heritable and correlated with methane emissions and feed intake. This research is part of a flagship program funded by the global research alliance to disseminate global access to technologies that lower greenhouse gas emissions in ruminant livestock.

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Recent Developments in Light-Emitting Polymers

MRS Bulletin ◽

10.1557/mrs2002.144 ◽

2002 ◽

Vol 27 (6) ◽

pp. 451-455 ◽

Cited By ~ 37

Author(s):

Ian D. Rees ◽

Kay L. Robinson ◽

Andrew B. Holmes ◽

Carl R. Towns ◽

Richard O'Dell

Keyword(s):

Mobile Applications ◽

First Generation ◽

Low Cost ◽

Major Focus ◽

Light Emitting ◽

Direct Patterning ◽

Ink Jet ◽

Recent Developments ◽

Jet Printing ◽

New Generation

AbstractConjugated light-emitting polymers (LEPs) have real potential to serve as the active layer in a new generation of emissive displays. Emerging as lead candidates for first-generation displays are poly(1,4-phenylene vinylene)s (PPVs) and poly(9,9-dialkylfluorene)s, as well as other polyaromatic materials. The poly(fluorene)s are at present the most commercially developed of these LEP materials for red–green–blue (RGB) applications. The low power consumption of LEP devices in general makes them particularly suited to mobile applications. Combining solution-processable emissive polymers with direct-patterning methods such as ink-jet printing will lead to the possibility of low-cost, high-resolution displays. The synthesis and properties of PPVs and poly(9,9-dialkylfluorene)s are briefly reviewed in this article, with a major focus on recent developments.

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Optimization of Genotyping-by-sequencing (GBS) in Chrysanthemums: Selecting Proper Restriction Enzymes for GBS Library Construction

Korean Journal of Horticultural Science&Technology ◽

10.12972/kjhst.20180012 ◽

2018 ◽

Vol 36 (1) ◽

Cited By ~ 3

Keyword(s):

Genotyping By Sequencing ◽

Restriction Enzymes ◽

Library Construction

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A high-resolution consensus linkage map for barley based on GBS-derived genotypes

Genome ◽

10.1139/gen-2021-0055 ◽

2021 ◽

pp. 1-12

Author(s):

Amina Abed ◽

Ana Badea ◽

Aaron Beattie ◽

Raja Khanal ◽

James Tucker ◽

...

Keyword(s):

High Resolution ◽

Linkage Map ◽

Low Cost ◽

Genotyping By Sequencing ◽

Average Density ◽

Genomic Research ◽

Consensus Map ◽

Genetic Studies ◽

Integrated Map ◽

The Mean

As genotyping-by-sequencing (GBS) is widely used in barley genetic studies, the translation of the physical position of GBS-derived SNPs into accurate genetic positions has become relevant. The main aim of this study was to develop a high-resolution consensus linkage map based on GBS-derived SNPs. The construction of this integrated map involved 11 bi-parental populations composed of 3743 segregating progenies. We adopted a uniform set of SNP-calling and filtering conditions to identify 50 875 distinct SNPs segregating in at least one population. These SNPs were grouped into 18 580 non-redundant SNPs (bins). The resulting consensus linkage map spanned 1050.1 cM, providing an average density of 17.7 bins and 48.4 SNPs per cM. The consensus map is characterized by the absence of large intervals devoid of marker coverage (significant gaps), the largest interval between bins was only 3.7 cM and the mean distance between adjacent bins was 0.06 cM. This high-resolution linkage map will contribute to several applications in genomic research, such as providing useful information on the recombination landscape for QTLs/genes identified via GWAS or ensuring a uniform distribution of SNPs when developing low-cost genotyping tools offering a limited number of markers.

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Adapting Genotyping-by-Sequencing for Rice F2 Populations

10.1101/055798 ◽

2016 ◽

Cited By ~ 1

Author(s):

Tomoyuki Furuta ◽

Motoyuki Ashikari ◽

Kshirod K. Jena ◽

Kazuyuki Doi ◽

Stefan Reuscher

Keyword(s):

Low Cost ◽

Genotyping By Sequencing ◽

Cost Effective ◽

Snp Markers ◽

Reduced Representation ◽

F2 Population ◽

Wild Rice Species ◽

Miseq Platform ◽

Mapping Populations ◽

Genotype A

ABSTRACTRapid and cost-effective genotyping of large mapping populations can be achieved by sequencing a reduced representation of the genome of every individual in a given population and using that information to generate genetic markers. A customized genotyping-by-sequencing (GBS) pipeline was developed to genotype a rice F2 population from a cross of Oryza sativa ssp. japonica cv. Nipponbare and the African wild rice species Oryza longistaminata. While most GBS pipelines aim to analyze mainly homozygous populations we attempted to genotype a highly heterozygous F2 population. We show how species-and population-specific improvements of established protocols can drastically increase sample throughput and genotype quality. Using as few as 50,000 reads for some individuals (134,000 reads on average) we were able to generate up to 8,154 informative SNP markers in 1,081 F2 individuals. Additionally, the effects of enzyme choice, read coverage and data post-processing are evaluated. Using GBS-derived markers we were able to assemble a genetic map of 1,536 cM. To demonstrate the usefulness of our GBS pipeline we determined QTL for the number of tillers. We were able to map four QTLs to chromosomes 1, 3, 4 and 8 and confirm their effects using introgression lines. We provide an example of how to successfully use GBS with heterozygous F2 populations. By using the comparatively low-cost MiSeq platform we show that the GBS method is flexible and cost-effective even for smaller laboratories

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Genotipado por secuenciación de variedades tradicionales de Theobroma cacao (Malvaceae) del Estado de Tabasco, México

Botanical Sciences ◽

10.17129/botsci.2258 ◽

2019 ◽

Vol 97 (3) ◽

pp. 381

Author(s):

Jorge Ricaño-Rodríguez ◽

Enrique Hipólito-Romero ◽

José M. Ramos-Prado ◽

Eliezer Cocoletzi-Vásquez

Keyword(s):

Single Nucleotide Polymorphisms ◽

Theobroma Cacao ◽

Genotyping By Sequencing ◽

Restriction Enzymes ◽

Nucleotide Polymorphisms ◽

Minimum Evolution ◽

Single Nucleotide ◽

Coding Regions ◽

Traditional Agroforestry

Background: Single nucleotide polymorphisms (SNPs) have been identified in Theobroma cacao through a genotyping-by-sequencing approach. Through this research it is shared for the first time a set of results related to genetic variability and nature of conserved coding regions of reduced nucleotide sequences of mexican native varieties of cocoa.Hypothesis: Obtaining reduced genomes of T. cacao specimens by restriction enzymes (REs) allows the characterization of single nucleotide polymorphisms (SNPs) as well as conserved coding regions (CDs).Species of study and dates: Theobroma cacao L. (Malvaceae)Study site: Theobroma cacao twigs came from traditional agroforestry plots located in the municipalities of Cardenas, Huimanguillo, Comalcalco, Paraiso, Jalpa de Mendez and Cunduacan, Tabasco, as well as Ixtacomitan and Pichucalco, Chiapas, Mexico; and they were collected and grafted among May and June from 2018.Methods: A method of genotyping-by-sequencing for the characterization of biobanks was developed. Filtering of crude sequences, genomic assembly, identification of SNPs, taxonomic molecular characterization and characterization of coding regions as well as minimum evolution of protein transcripts were performed.Results: Theobroma cacao samples showed different SNPs percentages (2 – 11 %) and the molecular evolution analyzes suggested similar maximum compound probabilities respect to their phylogeny. Conserved sequences were observed in the genomes´ coding regions, which suggest heuristic ontological predictions that have been evolutionarily regrouped in five clusters related to transcription processes and secondary metabolism.Conclusions: The GBS method allows to identify SNPs in cocoa. The characterization of reduced genomes determined the structural and transcriptional correlation between the samples and the reference genome of cacao Criollo.

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