Reference Genome Sequencing and Advances in Genomic Resources in Common Wheat–Chromosome 6B Project in Japan

The whole genome sequencing (WGS) has become a crucial tool in understanding genome structure and genetic variation. The MinION sequencing of Oxford Nanopore Technologies (ONT) is an excellent approach for performing WGS and it has advantages in comparison with other Next-Generation Sequencing (NGS): It is relatively inexpensive, portable, has simple library preparation, can be monitored in real-time, and has no theoretical limits on reading length. Sorghum bicolor (L.) Moench is diploid (2n = 2x = 20) with a genome size of about 730 Mb, and its genome sequence information is released in the Phytozome database. Therefore, sorghum can be used as a good reference. However, plant species have complex and large genomes when compared to animals or microorganisms. As a result, complete genome sequencing is difficult for plant species. MinION sequencing that produces long-reads can be an excellent tool for overcoming the weak assembly of short-reads generated from NGS by minimizing the generation of gaps or covering the repetitive sequence that appears on the plant genome. Here, we conducted the genome sequencing for S. bicolor cv. BTx623 while using the MinION platform and obtained 895,678 reads and 17.9 gigabytes (Gb) (ca. 25× coverage of reference) from long-read sequence data. A total of 6124 contigs (covering 45.9%) were generated from Canu, and a total of 2661 contigs (covering 50%) were generated from Minimap and Miniasm with a Racon through a de novo assembly using two different tools and mapped assembled contigs against the sorghum reference genome. Our results provide an optimal series of long-read sequencing analysis for plant species while using the MinION platform and a clue to determine the total sequencing scale for optimal coverage that is based on various genome sizes.

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Building a model: developing genomic resources for common milkweed (Asclepias syriaca) with low coverage genome sequencing

BMC Genomics ◽

10.1186/1471-2164-12-211 ◽

2011 ◽

Vol 12 (1) ◽

Cited By ~ 74

Author(s):

Shannon CK Straub ◽

Mark Fishbein ◽

Tatyana Livshultz ◽

Zachary Foster ◽

Matthew Parks ◽

...

Keyword(s):

Genome Sequencing ◽

Asclepias Syriaca ◽

Genomic Resources ◽

Common Milkweed Asclepias Syriaca ◽

Low Coverage

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Integration of chicken genomic resources to enable whole-genome sequencing

Cytogenetic and Genome Research ◽

10.1159/000075766 ◽

2003 ◽

Vol 102 (1-4) ◽

pp. 297-303 ◽

Cited By ~ 12

Author(s):

J. Aerts ◽

R. Crooijmans ◽

S. Cornelissen ◽

K. Hemmatian ◽

T. Veenendaal ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Whole Genome ◽

Genomic Resources

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BarleyVarDB: a database of barley genomic variation

Database ◽

10.1093/database/baaa091 ◽

2020 ◽

Vol 2020 ◽

Author(s):

Cong Tan ◽

Brett Chapman ◽

Penghao Wang ◽

Qisen Zhang ◽

Gaofeng Zhou ◽

...

Keyword(s):

Genome Sequencing ◽

Reference Genome ◽

Agronomic Traits ◽

Genetic Research ◽

Pcr Primers ◽

Genomic Variation ◽

Whole Genome ◽

Hordeum Vulgare L ◽

High Coverage ◽

Barley Genome

Abstract Barley (Hordeum vulgare L.) is one of the first domesticated grain crops and represents the fourth most important cereal source for human and animal consumption. BarleyVarDB is a database of barley genomic variation. It can be publicly accessible through the website at http://146.118.64.11/BarleyVar. This database mainly provides three sets of information. First, there are 57 754 224 single nuclear polymorphisms (SNPs) and 3 600 663 insertions or deletions (InDels) included in BarleyVarDB, which were identified from high-coverage whole genome sequencing of 21 barley germplasm, including 8 wild barley accessions from 3 barley evolutionary original centers and 13 barley landraces from different continents. Second, it uses the latest barley genome reference and its annotation information publicly accessible, which has been achieved by the International Barley Genome Sequencing Consortium (IBSC). Third, 522 212 whole genome-wide microsatellites/simple sequence repeats (SSRs) were also included in this database, which were identified in the reference barley pseudo-molecular genome sequence. Additionally, several useful web-based applications are provided including JBrowse, BLAST and Primer3. Users can design PCR primers to asses polymorphic variants deposited in this database and use a user-friendly interface for accessing the barley reference genome. We envisage that the BarleyVarDB will benefit the barley genetic research community by providing access to all publicly available barley genomic variation information and barley reference genome as well as providing them with an ultra-high density of SNP and InDel markers for molecular breeding and identification of functional genes with important agronomic traits in barley. Database URL: http://146.118.64.11/BarleyVar

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A cytogenetically based physical map of chromosome 1B in common wheat

Genome ◽

10.1139/g93-075 ◽

1993 ◽

Vol 36 (3) ◽

pp. 548-554 ◽

Cited By ~ 51

Author(s):

R. S. Kota ◽

K. S. Gill ◽

B. S. Gill ◽

T. R. Endo

Keyword(s):

Genetic Markers ◽

Common Wheat ◽

Hexaploid Wheat ◽

Genetic Linkage ◽

Genetic Linkage Map ◽

Physical Map ◽

Wheat Chromosome ◽

Homozygous Deletion ◽

Genetic Maps ◽

Rflp Markers

We have constructed a cytogenetically based physical map of chromosome 1B in common wheat by utilizing a total of 18 homozygous deletion stocks. It was possible to divide chromosome 1B into 17 subregions. Nineteen genetic markers are physically mapped to nine subregions of chromosome 1B. Comparison of the cytological map of chromosome 1B with an RFLP-based genetic linkage map of Triticum tauschii revealed that the linear order of the genetic markers was maintained between chromosome 1B of hexaploid wheat and 1D of T. tauschii. Striking differences were observed between the physical and genetic maps in relation to the relative distances between the genetic markers. The genetic markers clustered in the middle of the genetic map were physically located in the distal regions of both arms of chromosome 1B. It is unclear whether the increased recombination in the distal regions of chromosome 1B is due to specific regions of increased recombination or a more broadly distributed increase in recombination in the distal regions of Triticeae chromosomes.Key words: common wheat, chromosome 1B, homozygous deletion lines, physical map, RFLP markers.

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A mini-atlas of gene expression for the domestic goat (Capra hircus) reveals transcriptional differences in immune signatures between sheep and goats

10.1101/711127 ◽

2019 ◽

Cited By ~ 2

Author(s):

Charity Muriuki ◽

Stephen J. Bush ◽

Mazdak Salavati ◽

Mary E.B. McCulloch ◽

Zofia M. Lisowski ◽

...

Keyword(s):

Gene Expression ◽

Reference Genome ◽

Expression Profiles ◽

Expression Patterns ◽

Small Ruminants ◽

Capra Hircus ◽

Specific Cell ◽

Domestic Goat ◽

Protein Coding ◽

Genomic Resources

AbstractGoats (Capra hircus) are an economically important livestock species providing meat and milk across the globe. They are of particular importance in tropical agri-systems contributing to sustainable agriculture, alleviation of poverty, social cohesion and utilisation of marginal grazing. There are excellent genetic and genomic resources available for goats, including a highly contiguous reference genome (ARS1). However, gene expression information is limited in comparison to other ruminants. To support functional annotation of the genome and comparative transcriptomics we created a mini-atlas of gene expression for the domestic goat. RNA-Seq analysis of 22 transcriptionally rich tissues and cell-types detected the majority (90%) of predicted protein-coding transcripts and assigned informative gene names to more than 1000 previously unannotated protein-coding genes in the current reference genome for goat (ARS1). Using network-based cluster analysis we grouped genes according to their expression patterns and assigned those groups of co-expressed genes to specific cell populations or pathways. We describe clusters of genes expressed in the gastro-intestinal tract and provide the expression profiles across tissues of a subset of genes associated with functional traits. Comparative analysis of the goat atlas with the larger sheep gene expression atlas dataset revealed transcriptional differences between the two species in macrophage-associated signatures. The goat transcriptomic resource complements the large gene expression dataset we have generated for sheep and contributes to the available genomic resources for interpretation of the relationship between genotype and phenotype in small ruminants.

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Assessment the Quality of Genome Assemblies by using QUAST Tool for Metagenomics

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.e6435.038620 ◽

2020 ◽

Vol 8 (6) ◽

pp. 4253-4259

Keyword(s):

Genome Sequencing ◽

Reference Genome ◽

Assessment Tool ◽

Quality Assessment Tool ◽

Assembly Evaluation ◽

Assembly Algorithms ◽

Genome Assemblies ◽

Modern Tool ◽

Assembly Software

Number of assembly algorithms have emerged out but due to constraints of genome sequencing techniques no one is perfect. Various methods for assembler’s comparison have been developed, but none is yet a recognized standard. The problem of evaluating assemblies of formerly unsequenced species has not been considered, because mostly existing methods for comparing assemblies are only applicable to new assemblies of finished genomes. For comparing and evaluating genome assemblies we have used QUAST (Quality Assessment Tool). This tool is used to assess the quality of leading assembly software by evaluating quality metrics. Assemblies with a reference genome, as well as without a reference can be evaluated by QUAST tool. For genome assembly evaluation based on alignment of contigs to a reference, it is a modern tool. In this study we demonstrate QUAST performance by comparing several leading genome assemblers on three metagenomic datasets.

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