Genomic Variation in Korean japonica Rice Varieties

Next-generation sequencing technologies have enabled the discovery of numerous sequence variations among closely related crop varieties. We analyzed genome resequencing data from 24 Korean temperate japonica rice varieties and discovered 954,233 sequence variations, including 791,121 single nucleotide polymorphisms (SNPs) and 163,112 insertions/deletions (InDels). On average, there was one variant per 391 base-pairs (bp), a variant density of 2.6 per 1 kbp. Of the InDels, 10,860 were longer than 20 bp, which enabled conversion to markers resolvable on an agarose gel. The effect of each variant on gene function was predicted using the SnpEff program. The variants were categorized into four groups according to their impact: high, moderate, low, and modifier. These groups contained 3524 (0.4%), 27,656 (2.9%), 24,875 (2.6%), and 898,178 (94.1%) variants, respectively. To test the accuracy of these data, eight InDels from a pre-harvest sprouting resistance QTL (qPHS11) target region, four highly polymorphic InDels, and four functional sequence variations in known agronomically important genes were selected and successfully developed into markers. These results will be useful to develop markers for marker-assisted selection, to select candidate genes in map-based cloning, and to produce efficient high-throughput genome-wide genotyping systems for Korean temperate japonica rice varieties.

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Breeding Temperate Japonica Rice Varieties Adaptable to Tropical Regions: Progress and Prospects

Agronomy ◽

10.3390/agronomy11112253 ◽

2021 ◽

Vol 11 (11) ◽

pp. 2253

Author(s):

Myrish Pacleb ◽

O-Young Jeong ◽

Jeom-Sig Lee ◽

Thelma Padolina ◽

Rustum Braceros ◽

...

Keyword(s):

The Philippines ◽

Tropical Region ◽

Japonica Rice ◽

Rice Varieties ◽

Temperate Japonica ◽

Tropical Regions ◽

Tropical Environments ◽

Increasing Demand ◽

Northeast Asian ◽

The Tropics

Temperate japonica rice is mainly cultivated in temperate regions. Many temperate japonica varieties have a superior grain quality that is preferred in Northeast Asian countries such as Japan, Korea, and China. The changes in consumers’ preferences in Southeast Asia and Western countries has contributed to increasing the demand for temperate japonica. Most temperate japonica varieties developed in temperate regions typically exhibit extra-early flowering under the short-day conditions in the tropics, which usually results in severely reduced yields. Since 1992, we have been developing temperate japonica varieties that can adapt to tropical environments to meet the increasing demand for temperate japonica rice, having released six varieties in the Philippines. Especially, the yield of one of the temperate japonica varieties, Japonica 7, was comparable to the yields of leading indica varieties in the Philippines. Here, we discuss the current breeding initiatives and future plans for the development of tropical-region-bred temperate japonica rice.

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The humankind genome: from genetic diversity to the origin of human diseases

Genome ◽

10.1139/gen-2013-0125 ◽

2013 ◽

Vol 56 (12) ◽

pp. 705-716 ◽

Cited By ~ 11

Author(s):

Jose E. Belizário

Keyword(s):

Genetic Variants ◽

Association Studies ◽

Model Organism ◽

Copy Number Variations ◽

Genomic Variation ◽

Human Diseases ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Full Characterization ◽

Sequencing Technologies

Genome-wide association studies have failed to establish common variant risk for the majority of common human diseases. The underlying reasons for this failure are explained by recent studies of resequencing and comparison of over 1200 human genomes and 10 000 exomes, together with the delineation of DNA methylation patterns (epigenome) and full characterization of coding and noncoding RNAs (transcriptome) being transcribed. These studies have provided the most comprehensive catalogues of functional elements and genetic variants that are now available for global integrative analysis and experimental validation in prospective cohort studies. With these datasets, researchers will have unparalleled opportunities for the alignment, mining, and testing of hypotheses for the roles of specific genetic variants, including copy number variations, single nucleotide polymorphisms, and indels as the cause of specific phenotypes and diseases. Through the use of next-generation sequencing technologies for genotyping and standardized ontological annotation to systematically analyze the effects of genomic variation on humans and model organism phenotypes, we will be able to find candidate genes and new clues for disease’s etiology and treatment. This article describes essential concepts in genetics and genomic technologies as well as the emerging computational framework to comprehensively search websites and platforms available for the analysis and interpretation of genomic data.

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A hybrid pipeline for reconstruction and analysis of viral genomes at multi-organ level

GigaScience ◽

10.1093/gigascience/giaa086 ◽

2020 ◽

Vol 9 (8) ◽

Cited By ~ 4

Author(s):

Diogo Pratas ◽

Mari Toppinen ◽

Lari Pyöriä ◽

Klaus Hedman ◽

Antti Sajantila ◽

...

Keyword(s):

De Novo ◽

Sequence Data ◽

Ex Vivo ◽

Genomic Variation ◽

Nucleotide Polymorphisms ◽

Sensitive Data ◽

Viral Genomes ◽

Sequencing Technologies ◽

Multiple Organs ◽

Research Perspectives

Abstract Background Advances in sequencing technologies have enabled the characterization of multiple microbial and host genomes, opening new frontiers of knowledge while kindling novel applications and research perspectives. Among these is the investigation of the viral communities residing in the human body and their impact on health and disease. To this end, the study of samples from multiple tissues is critical, yet, the complexity of such analysis calls for a dedicated pipeline. We provide an automatic and efficient pipeline for identification, assembly, and analysis of viral genomes that combines the DNA sequence data from multiple organs. TRACESPipe relies on cooperation among 3 modalities: compression-based prediction, sequence alignment, and de novo assembly. The pipeline is ultra-fast and provides, additionally, secure transmission and storage of sensitive data. Findings TRACESPipe performed outstandingly when tested on synthetic and ex vivo datasets, identifying and reconstructing all the viral genomes, including those with high levels of single-nucleotide polymorphisms. It also detected minimal levels of genomic variation between different organs. Conclusions TRACESPipe’s unique ability to simultaneously process and analyze samples from different sources enables the evaluation of within-host variability. This opens up the possibility to investigate viral tissue tropism, evolution, fitness, and disease associations. Moreover, additional features such as DNA damage estimation and mitochondrial DNA reconstruction and analysis, as well as exogenous-source controls, expand the utility of this pipeline to other fields such as forensics and ancient DNA studies. TRACESPipe is released under GPLv3 and is available for free download at https://github.com/viromelab/tracespipe.

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Development of 454 New Kompetitive Allele-Specific PCR (KASP) Markers for Temperate japonica Rice Varieties

Plants ◽

10.3390/plants9111531 ◽

2020 ◽

Vol 9 (11) ◽

pp. 1531

Author(s):

Kyeong-Seong Cheon ◽

Young-Min Jeong ◽

Hyoja Oh ◽

Jun Oh ◽

Do-Yu Kang ◽

...

Keyword(s):

Agronomic Traits ◽

High Impact ◽

Japonica Rice ◽

Rice Varieties ◽

Breeding Programs ◽

Temperate Japonica ◽

Specific Pcr ◽

Allele Specific ◽

Allele Specific Pcr ◽

Kasp Markers

Temperate japonica rice varieties exhibit wide variation in the phenotypes of several important agronomic traits, including disease resistance, pre-harvest sprouting resistance, plant architecture, and grain quality, indicating the presence of genes contributing to favorable agronomic traits. However, gene mapping and molecular breeding has been hampered as a result of the low genetic diversity among cultivars and scarcity of polymorphic DNA markers. Single nucleotide polymorphism (SNP)-based kompetitive allele-specific PCR (KASP) markers allow high-throughput genotyping for marker-assisted selection and quantitative trait loci (QTL) mapping within closely related populations. Previously, we identified 740,566 SNPs and developed 771 KASP markers for Korean temperate japonica rice varieties. However, additional markers were needed to provide sufficient genome coverage to support breeding programs. In this study, the 740,566 SNPs were categorized according to their predicted impacts on gene function. The high-impact, moderate-impact, modifier, and low-impact groups contained 703 (0.1%), 20,179 (2.7%), 699,866 (94.5%), and 19,818 (2.7%) SNPs, respectively. A subset of 357 SNPs from the high-impact group was selected for initial KASP marker development, resulting in 283 polymorphic KASP markers. After incorporation of the 283 markers with the 771 existing markers in a physical map, additional markers were developed to fill genomic regions with large gaps between markers, and 171 polymorphic KASP markers were successfully developed from 284 SNPs. Overall, a set of 1225 KASP markers was produced. The markers were evenly distributed across the rice genome, with average marker density of 3.3 KASP markers per Mbp. The 1225 KASP markers will facilitate QTL/gene mapping and marker-assisted selection in temperate japonica rice breeding programs.

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QTL mapping for pre-harvest sprouting resistance in japonica rice varieties utilizing genome re-sequencing

Molecular Genetics and Genomics ◽

10.1007/s00438-020-01688-4 ◽

2020 ◽

Vol 295 (5) ◽

pp. 1129-1140 ◽

Cited By ~ 1

Author(s):

Kyeong-Seong Cheon ◽

Yong Jae Won ◽

Young-Min Jeong ◽

Youn-Young Lee ◽

Do-Yu Kang ◽

...

Keyword(s):

Qtl Mapping ◽

Japonica Rice ◽

Rice Varieties ◽

Sprouting Resistance

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Genotypic Variation in Nutrient Uptake Requirements of Rice Using the QUEFTS Model

Agronomy ◽

10.3390/agronomy11010026 ◽

2020 ◽

Vol 11 (1) ◽

pp. 26

Author(s):

Tao Sun ◽

Xin Yang ◽

Sheng Tang ◽

Kefeng Han ◽

Ping He ◽

...

Keyword(s):

Nutrient Uptake ◽

Field Experiments ◽

Hybrid Rice ◽

Genotypic Variation ◽

Tropical Soils ◽

Study Data ◽

Japonica Rice ◽

Rice Varieties ◽

Indica Hybrid Rice ◽

Validation Experiments

Nutrient requirements for single-season rice using the quantitative evaluation of the fertility of tropical soils (QUEFTS) model in China have been estimated in a previous study, which involved all the rice varieties; however, it is unclear whether a similar result can be obtained for different rice varieties. In this study, data were collected from field experiments conducted from 2016 to 2019 in Zhejiang Province, China. The dataset was separated into two parts: japonica/indica hybrid rice and japonica rice. To produce 1000 kg of grain, 13.5 kg N, 3.6 kg P, and 20.4 kg K were required in the above-ground plant dry matter for japonica/indica hybrid rice, and the corresponding internal efficiencies (IEs) were 74.0 kg grain per kg N, 279.1 kg grain per kg P, and 49.1 kg grain per kg K. For japonica rice, 17.6 kg N, 4.1 kg P, and 23.0 kg K were required to produce 1000 kg of grain, and the corresponding IEs were 56.8 kg grain per kg N, 244.6 kg grain per kg P, and 43.5 kg grain per kg K. Field validation experiments indicated that the QUEFTS model could be used to estimate nutrient uptake of different rice varieties. We suggest that variety should be taken into consideration when estimating nutrient uptake for rice using the QUEFTS model, which would improve this model.

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Transcriptomic profiling of wheat near-isogenic lines reveals candidate genes on chromosome 3A for pre-harvest sprouting resistance

BMC Plant Biology ◽

10.1186/s12870-021-02824-x ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Xingyi Wang ◽

Hui Liu ◽

Kadambot H. M. Siddique ◽

Guijun Yan

Keyword(s):

Candidate Genes ◽

Quantitative Trait ◽

Genomic Region ◽

Nucleotide Polymorphisms ◽

Near Isogenic Lines ◽

Gene Effects ◽

Isogenic Lines ◽

Trait Locus ◽

Grain Yield And Quality ◽

Sprouting Resistance

Abstract Background Pre-harvest sprouting (PHS) in wheat can cause severe damage to both grain yield and quality. Resistance to PHS is a quantitative trait controlled by many genes located across all 21 wheat chromosomes. The study targeted a large-effect quantitative trait locus (QTL) QPhs.ccsu-3A.1 for PHS resistance using several sets previously developed near-isogenic lines (NILs). Two pairs of NILs with highly significant phenotypic differences between the isolines were examined by RNA sequencing for their transcriptomic profiles on developing seeds at 15, 25 and 35 days after pollination (DAP) to identify candidate genes underlying the QTL and elucidate gene effects on PHS resistance. At each DAP, differentially expressed genes (DEGs) between the isolines were investigated. Results Gene ontology and KEGG pathway enrichment analyses of key DEGs suggested that six candidate genes underlie QPhs.ccsu-3A.1 responsible for PHS resistance in wheat. Candidate gene expression was further validated by quantitative RT-PCR. Within the targeted QTL interval, 16 genetic variants including five single nucleotide polymorphisms (SNPs) and 11 indels showed consistent polymorphism between resistant and susceptible isolines. Conclusions The targeted QTL is confirmed to harbor core genes related to hormone signaling pathways that can be exploited as a key genomic region for marker-assisted selection. The candidate genes and SNP/indel markers detected in this study are valuable resources for understanding the mechanism of PHS resistance and for marker-assisted breeding of the trait in wheat.

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Unexpected genomic, biosynthetic and species diversity of Streptomyces bacteria from bats in Arizona and New Mexico, USA

BMC Genomics ◽

10.1186/s12864-021-07546-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Cooper J. Park ◽

Nicole A. Caimi ◽

Debbie C. Buecher ◽

Ernest W. Valdez ◽

Diana E. Northup ◽

...

Keyword(s):

New Mexico ◽

Genetic Manipulation ◽

Distinct Species ◽

Biosynthetic Gene Cluster ◽

Genomic Variation ◽

Species Variation ◽

Nucleotide Polymorphisms ◽

Peptide Synthetases ◽

Genome Wide ◽

Diversity Estimates

Abstract Background Antibiotic-producing Streptomyces bacteria are ubiquitous in nature, yet most studies of its diversity have focused on free-living strains inhabiting diverse soil environments and those in symbiotic relationship with invertebrates. Results We studied the draft genomes of 73 Streptomyces isolates sampled from the skin (wing and tail membranes) and fur surfaces of bats collected in Arizona and New Mexico. We uncovered large genomic variation and biosynthetic potential, even among closely related strains. The isolates, which were initially identified as three distinct species based on sequence variation in the 16S rRNA locus, could be distinguished as 41 different species based on genome-wide average nucleotide identity. Of the 32 biosynthetic gene cluster (BGC) classes detected, non-ribosomal peptide synthetases, siderophores, and terpenes were present in all genomes. On average, Streptomyces genomes carried 14 distinct classes of BGCs (range = 9–20). Results also revealed large inter- and intra-species variation in gene content (single nucleotide polymorphisms, accessory genes and singletons) and BGCs, further contributing to the overall genetic diversity present in bat-associated Streptomyces. Finally, we show that genome-wide recombination has partly contributed to the large genomic variation among strains of the same species. Conclusions Our study provides an initial genomic assessment of bat-associated Streptomyces that will be critical to prioritizing those strains with the greatest ability to produce novel antibiotics. It also highlights the need to recognize within-species variation as an important factor in genetic manipulation studies, diversity estimates and drug discovery efforts in Streptomyces.

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Apollo: a sequencing-technology-independent, scalable and accurate assembly polishing algorithm

Bioinformatics ◽

10.1093/bioinformatics/btaa179 ◽

2020 ◽

Vol 36 (12) ◽

pp. 3669-3679 ◽

Cited By ~ 3

Author(s):

Can Firtina ◽

Jeremie S Kim ◽

Mohammed Alser ◽

Damla Senol Cali ◽

A Ercument Cicek ◽

...

Keyword(s):

Genome Analysis ◽

Supplementary Information ◽

Third Generation ◽

Sequencing Technology ◽

Base Pairs ◽

Sequencing Technologies ◽

Third Generation Sequencing ◽

Long Reads ◽

Generation Sequencing ◽

Large Genomes

Abstract Motivation Third-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs. These long reads are used to construct an assembly (i.e. the subject’s genome), which is further used in downstream genome analysis. Unfortunately, third-generation sequencing technologies have high sequencing error rates and a large proportion of base pairs in these long reads is incorrectly identified. These errors propagate to the assembly and affect the accuracy of genome analysis. Assembly polishing algorithms minimize such error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e. read-to-assembly alignment information). However, current assembly polishing algorithms can only polish an assembly using reads from either a certain sequencing technology or a small assembly. Such technology-dependency and assembly-size dependency require researchers to (i) run multiple polishing algorithms and (ii) use small chunks of a large genome to use all available readsets and polish large genomes, respectively. Results We introduce Apollo, a universal assembly polishing algorithm that scales well to polish an assembly of any size (i.e. both large and small genomes) using reads from all sequencing technologies (i.e. second- and third-generation). Our goal is to provide a single algorithm that uses read sets from all available sequencing technologies to improve the accuracy of assembly polishing and that can polish large genomes. Apollo (i) models an assembly as a profile hidden Markov model (pHMM), (ii) uses read-to-assembly alignment to train the pHMM with the Forward–Backward algorithm and (iii) decodes the trained model with the Viterbi algorithm to produce a polished assembly. Our experiments with real readsets demonstrate that Apollo is the only algorithm that (i) uses reads from any sequencing technology within a single run and (ii) scales well to polish large assemblies without splitting the assembly into multiple parts. Availability and implementation Source code is available at https://github.com/CMU-SAFARI/Apollo. Supplementary information Supplementary data are available at Bioinformatics online.

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