Novel QTLs for salinity tolerance revealed by genome-wide association studies of biomass, chlorophyll and tissue ion content in 176 rice landraces from Bangladesh

Farmland is on the decline and worldwide food security is at risk. Rice is the staple of choice for over half the Earth’s people. To sustain current demands and ascertain a food secure future, substandard farmland affected by abiotic stresses must be utilized. For rapid crop improvement, a broader understanding of polygenic traits like stress tolerance and crop yield is indispensable. To this end, the hidden diversity of resilient and neglected wild varieties must be traced back to their genetic roots. In this study, we separately assayed 11 phenotypes in a panel of 176 diverse accessions predominantly comprised of local landraces from Bangladesh. We compiled high resolution sequence data for these accessions. We collectively studied the ties between the observed phenotypic differences and the examined additive genetic effects underlying these variations. We applied a fixed effect model to associate phenotypes with genotypes on a genomic scale. Discovered QTLs were mapped to known genes. Our explorations yielded 13 QTLs related to various traits in multiple trait classes. 10 identified QTLs were equivalent to findings from previous studies. Integrative analysis assumes potential novel functionality for a number of candidate genes. These findings will usher novel avenues for the bioengineering of high yielding crops of the future fortified with genetic defenses against abiotic stressors.

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Comprehensive analysis and genome-wide association studies of biomass, chlorophyll, seed and salinity tolerance related traits in rice highlight genetic hotspots for crop improvement

10.1101/2020.12.24.424354 ◽

2020 ◽

Author(s):

Md Nafis Ul Alam ◽

G.M. Nurnabi Azad Jewel ◽

Tomalika Azim ◽

Zeba I. Seraj

Keyword(s):

Candidate Genes ◽

Sequence Data ◽

Expression Profiles ◽

Association Studies ◽

Crop Improvement ◽

Gene Expression Profiles ◽

Fixed Effect Model ◽

Specific Gene ◽

Genome Wide Association Studies ◽

Multiple Trait

AbstractFarmland is on the decline and worldwide food security is at risk. Rice is the staple of choice for over half the Earth’s people. To sustain current demands and ascertain a food secure future, substandard farmland affected by abiotic stresses must be utilized. For rapid crop improvement, a broader understanding of polygenic traits like stress tolerance and crop yield is indispensable. To this end, the hidden diversity of resilient and neglected wild varieties must be traced back to their genetic roots. In this study, we separately assayed 15 phenotypes in a panel of 176 diverse accessions predominantly comprised of local landraces from Bangladesh. We compiled high resolution sequence data for these accessions. We collectively studied the ties between the observed phenotypic differences and the examined additive genetic effects underlying these variations. We applied a sophisticated fixed effect model to associate phenotypes with genotypes on a genomic scale. Discovered QTLs were mapped to known genes. Candidate genes were sorted by tissue specific gene expression profiles and protein level consequence of existing polymorphisms. Our explorations yielded 17 QTLs related to various traits in multiple trait classes. 12 identified QTLs were equivalent to findings from previous studies. Integrative analysis assumes novel functionality for 21 candidate genes on multiple evidence levels. These findings will usher novel avenues for the bioengineering of high yielding crops of the future fortified with genetic defenses against abiotic stressors.

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SSR Marker Based Genetic Diversity Analysis and SNP Haplotyping of Genes Associating Abiotic and Biotic Stress Tolerance, Rice Growth and Development and Yield Across 93 Rice Landraces

10.21203/rs.3.rs-466659/v1 ◽

2021 ◽

Author(s):

Smitha Kunhiraman Vasumathy ◽

Manickavelu Alagu

Keyword(s):

Genetic Diversity ◽

Stress Tolerance ◽

Growth And Development ◽

Haplotype Analysis ◽

Association Studies ◽

Abiotic Stress Tolerance ◽

Crop Improvement ◽

World Population ◽

Genome Wide Association Studies ◽

Rice Landraces

Abstract I. Background: As rice is the staple food for more than half of the world population, enhancing grain yield irrespective of the variable climatic conditions is indispensable. Many of the traditionally cultivated rice landraces are well adapted to severe environmental conditions and have high genetic diversity that could play an important role in crop improvement.II. Methods and Results: The present study disclosed high level of genetic diversity among the unexploited rice landraces cultivated by farmers of Kerala. Twelve polymorphic markers detected a total of seventy- seven alleles with an average of 6.416 alleles per locus. PIC value ranged from 0.459 to 0.809 and to differentiate the rice genotypes, RM 242 was found to be the most appropriate marker with the highest value of 0.809. The current study indicated that the rice landraces were highly diverse with higher values of the effective number of alleles, PIC, and Shannon information index and utilizing these informative SSR markers for future molecular characterization and population genetic studies in rice landraces are advisable. Haplotypes are sets of genomic regions within a chromosome that are inherited together and haplotype-based breeding is a promising strategy for designing next-generation rice varieties. Here, haplotype analysis explored 270 haplotype blocks and 775 haplotypes from all the chromosomes of landraces under study. The number of SNPs in each haplotype block ranged from two to 28. Haplotypes of genes related to biotic and abiotic stress tolerance, yield-enhancing, and growth and development in rice landraces were also elucidated in the current study.III. Conclusions: The present investigation revealed genetic diversity of rice landraces and the haplotype analysis will open the way for genome wide association studies, QTL identification, and marker assisted selection in the unexplored rice landraces collected from Kerala.

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Whole-Genome Sequencing of the NARO World Rice Core Collection (WRC) as the Basis for Diversity and Association Studies

Plant and Cell Physiology ◽

10.1093/pcp/pcaa019 ◽

2020 ◽

Vol 61 (5) ◽

pp. 922-932 ◽

Cited By ~ 3

Author(s):

N Tanaka ◽

M Shenton ◽

Y Kawahara ◽

M Kumagai ◽

H Sakai ◽

...

Keyword(s):

Genetic Diversity ◽

Core Collection ◽

Sequence Data ◽

Association Studies ◽

Crop Improvement ◽

Heading Date ◽

Principal Component ◽

Genome Wide Association Studies ◽

Whole Genome ◽

Population Structure Analysis

Abstract Genebanks provide access to diverse materials for crop improvement. To utilize and evaluate them effectively, core collections, such as the World Rice Core Collection (WRC) in the Genebank at the National Agriculture and Food Research Organization, have been developed. Because the WRC consists of 69 accessions with a high degree of genetic diversity, it has been used for >300 projects. To allow deeper investigation of existing WRC data and to further promote research using Genebank rice accessions, we performed whole-genome resequencing of these 69 accessions, examining their sequence variation by mapping against the Oryza sativa ssp. japonica Nipponbare genome. We obtained a total of 2,805,329 single nucleotide polymorphisms (SNPs) and 357,639 insertion–deletions. Based on the principal component analysis and population structure analysis of these data, the WRC can be classified into three major groups. We applied TASUKE, a multiple genome browser to visualize the different WRC genome sequences, and classified haplotype groups of genes affecting seed characteristics and heading date. TASUKE thus provides access to WRC genotypes as a tool for reverse genetics. We examined the suitability of the compact WRC population for genome-wide association studies (GWASs). Heading date, affected by a large number of quantitative trait loci (QTLs), was not associated with known genes, but several seed-related phenotypes were associated with known genes. Thus, for QTLs of strong effect, the compact WRC performed well in GWAS. This information enables us to understand genetic diversity in 37,000 rice accessions maintained in the Genebank and to find genes associated with different phenotypes. The sequence data have been deposited in DNA Data Bank of Japan Sequence Read Archive (DRA) (Supplementary Table S1).

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Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Nature ◽

10.1038/s41586-021-03205-y ◽

2021 ◽

Vol 590 (7845) ◽

pp. 290-299 ◽

Cited By ~ 22

Author(s):

Daniel Taliun ◽

◽

Daniel N. Harris ◽

Michael D. Kessler ◽

Jedidiah Carlson ◽

...

Keyword(s):

Rare Variants ◽

Sequence Data ◽

Association Studies ◽

Genotype Imputation ◽

Genome Wide Association Studies ◽

Phenotypic Data ◽

Treatment And Prevention ◽

Genome Wide ◽

Diverse Backgrounds ◽

Unmapped Reads

AbstractThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

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Genome-wide association studies of 14 agronomic traits in rice landraces

Nature Genetics ◽

10.1038/ng.695 ◽

2010 ◽

Vol 42 (11) ◽

pp. 961-967 ◽

Cited By ~ 1156

Author(s):

Xuehui Huang ◽

Xinghua Wei ◽

Tao Sang ◽

Qiang Zhao ◽

Qi Feng ◽

...

Keyword(s):

Agronomic Traits ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Rice Landraces ◽

Genome Wide

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High-throughput phenotyping reveals a link between transpiration efficiency and transpiration restriction under high evaporative demand and new loci controlling water use-related traits in African rice, Oryza glaberrima Steud.

10.1101/2021.11.28.470237 ◽

2021 ◽

Author(s):

Pablo Affortit ◽

Branly Effa Effa ◽

Mame Sokhatil Ndoye ◽

Daniel Moukouanga ◽

Nathalie Luchaire ◽

...

Keyword(s):

Water Use Efficiency ◽

Water Use ◽

Association Studies ◽

Crop Improvement ◽

Oryza Glaberrima ◽

Genome Wide Association Studies ◽

Transpiration Efficiency ◽

Evaporative Demand ◽

African Rice ◽

Use Efficiency

Because water availability is the most important environmental factor limiting crop production, improving water use efficiency, the amount of carbon fixed per water used, is a major target for crop improvement. In rice, the genetic bases of transpiration efficiency, the derivation of water use efficiency at the whole-plant scale, and its putative component trait transpiration restriction under high evaporative demand, remain unknown. These traits were measured in a panel of 147 African rice Oryza glaberrima genotypes, known as potential sources of tolerance genes to biotic and abiotic stresses. Our results reveal that higher transpiration efficiency is associated with transpiration restriction in African rice. Detailed measurements in a subset of highly differentiated genotypes confirmed these associations and suggested that the root to shoot ratio played an important role in transpiration restriction. Genome wide association studies identified marker-trait associations for transpiration response to evaporative demand, transpiration efficiency and its residuals, that links to genes involved in water transport and cell wall patterning. Our data suggest that root shoot partitioning is an important component of transpiration restriction that has a positive effect on transpiration efficiency in African rice. Both traits are heritable and define targets for breeding rice with improved water use strategies.

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EGFR Polymorphism and Survival of NSCLC Patients Treated with TKIs: A Systematic Review and Meta-Analysis

Journal of Oncology ◽

10.1155/2020/1973241 ◽

2020 ◽

Vol 2020 ◽

pp. 1-14 ◽

Cited By ~ 2

Author(s):

Vladimir Jurisic ◽

Vladimir Vukovic ◽

Jasmina Obradovic ◽

Lyudmila F. Gulyaeva ◽

Nikolay E. Kushlinskii ◽

...

Keyword(s):

Kinase Inhibitor ◽

Association Studies ◽

Meta Analysis ◽

Growth Factor Receptor ◽

Fixed Effect Model ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Ca Repeat ◽

Meta Analyses ◽

Nsclc Patients

Tyrosine kinase inhibitor- (TKI-) based therapy revolutionized the overall survival and the quality of life in non-small-cell lung cancer (NSCLC) patients that have epidermal growth factor receptor (EGFR) mutations. However, EGFR is a highly polymorphic and mutation-prone gene, with over 1200 single nucleotide polymorphisms (SNPs). Since the role of EFGR polymorphism on the treatment outcome is still a matter of debate, this research analyzed the available literature data, according to the PRISMA guidelines for meta-analyses. Research includes PubMed, Scopus, ISI Web of Science, and 14 of genome-wide association studies (GWAS) electronic databases in order to provide quantitative assessment of the association between ten investigated EGFR SNPs and the survival of NSCLC patients. The pooled HR and their 95% CI for OS and PFS for different EGFR polymorphisms using a random or fixed effect model based on the calculated heterogeneity between the studies was applied. The longest and the shortest median OSs were reported for the homozygous wild genotype and a variant allele carriers for rs712829 (-216G>T), respectively. Quantitative synthesis in our study shows that out of ten investigated EGFR SNPs (rs11543848, rs11568315, rs11977388, rs2075102, rs2227983, rs2293347, rs4947492, rs712829, rs712830, and rs7809028), only four, namely, rs712829 (-216G>T), rs11568315 (CA repeat), rs2293347 (D994D), and rs4947492, have been reported to affect the outcome of TKI-based NSCLC treatment. Of these, only -216G>T and variable CA repeat polymorphisms have been confirmed by meta-analysis of available data to significantly affect OS and PFS in gefitinib- or erlotinib-treated NSCLC patients.

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ADDO: a comprehensive toolkit to detect, classify and visualize additive and non-additive quantitative trait loci

Bioinformatics ◽

10.1093/bioinformatics/btz786 ◽

2019 ◽

Vol 36 (5) ◽

pp. 1517-1521

Author(s):

Leilei Cui ◽

Bin Yang ◽

Nikolas Pontikos ◽

Richard Mott ◽

Lusheng Huang

Keyword(s):

Quantitative Trait Loci ◽

Quantitative Trait ◽

Association Studies ◽

Genetic Effects ◽

Supplementary Information ◽

Genome Wide Association Studies ◽

Additive Effects ◽

A Genome ◽

Trait Loci ◽

Additive Genetic Effects

Abstract Motivation During the past decade, genome-wide association studies (GWAS) have been used to map quantitative trait loci (QTLs) underlying complex traits. However, most GWAS focus on additive genetic effects while ignoring non-additive effects, on the assumption that most QTL act additively. Consequently, QTLs driven by dominance and other non-additive effects could be overlooked. Results We developed ADDO, a highly efficient tool to detect, classify and visualize QTLs with additive and non-additive effects. ADDO implements a mixed-model transformation to control for population structure and unequal relatedness that accounts for both additive and dominant genetic covariance among individuals, and decomposes single-nucleotide polymorphism effects as either additive, partial dominant, dominant or over-dominant. A matrix multiplication approach is used to accelerate the computation: a genome scan on 13 million markers from 900 individuals takes about 5 h with 10 CPUs. Analysis of simulated data confirms ADDO’s performance on traits with different additive and dominance genetic variance components. We showed two real examples in outbred rat where ADDO identified significant dominant QTL that were not detectable by an additive model. ADDO provides a systematic pipeline to characterize additive and non-additive QTL in whole genome sequence data, which complements current mainstream GWAS software for additive genetic effects. Availability and implementation ADDO is customizable and convenient to install and provides extensive analytics and visualizations. The package is freely available online at https://github.com/LeileiCui/ADDO. Supplementary information Supplementary data are available at Bioinformatics online.

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Advances in Omics Approaches for Abiotic Stress Tolerance in Tomato

Biology ◽

10.3390/biology8040090 ◽

2019 ◽

Vol 8 (4) ◽

pp. 90 ◽

Cited By ~ 7

Author(s):

Juhi Chaudhary ◽

Praveen Khatri ◽

Pankaj Singla ◽

Surbhi Kumawat ◽

Anu Kumari ◽

...

Keyword(s):

Abiotic Stress ◽

Stress Tolerance ◽

Association Studies ◽

Abiotic Stress Tolerance ◽

Crop Improvement ◽

Genetic Regulatory Networks ◽

Plant Responses ◽

Genome Wide Association Studies ◽

Market Demand ◽

Efficient Utilization

Tomato, one of the most important crops worldwide, has a high demand in the fresh fruit market and processed food industries. Despite having considerably high productivity, continuous supply as per the market demand is hard to achieve, mostly because of periodic losses occurring due to biotic as well as abiotic stresses. Although tomato is a temperate crop, it is grown in almost all the climatic zones because of widespread demand, which makes it challenge to adapt in diverse conditions. Development of tomato cultivars with enhanced abiotic stress tolerance is one of the most sustainable approaches for its successful production. In this regard, efforts are being made to understand the stress tolerance mechanism, gene discovery, and interaction of genetic and environmental factors. Several omics approaches, tools, and resources have already been developed for tomato growing. Modern sequencing technologies have greatly accelerated genomics and transcriptomics studies in tomato. These advancements facilitate Quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS). However, limited efforts have been made in other omics branches like proteomics, metabolomics, and ionomics. Extensive cataloging of omics resources made here has highlighted the need for integration of omics approaches for efficient utilization of resources and a better understanding of the molecular mechanism. The information provided here will be helpful to understand the plant responses and the genetic regulatory networks involved in abiotic stress tolerance and efficient utilization of omics resources for tomato crop improvement.

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A global overview of pleiotropy and genetic architecture in complex traits

10.1101/500090 ◽

2018 ◽

Cited By ~ 19

Author(s):

Kyoko Watanabe ◽

Sven Stringer ◽

Oleksandr Frei ◽

Maša Umićević Mirkov ◽

Tinca J.C. Polderman ◽

...

Keyword(s):

Genetic Variants ◽

Complex Traits ◽

Genetic Architecture ◽

Human Genetics ◽

Association Studies ◽

Regulatory Elements ◽

Genome Wide Association Studies ◽

Multiple Trait ◽

Current Availability ◽

Flanking Regions

ABSTRACTAfter a decade of genome-wide association studies (GWASs), fundamental questions in human genetics are still unanswered, such as the extent of pleiotropy across the genome, the nature of trait-associated genetic variants and the disparate genetic architecture across human traits. The current availability of hundreds of GWAS results provide the unique opportunity to gain insight into these questions. In this study, we harmonized and systematically analysed 4,155 publicly available GWASs. For a subset of well-powered GWAS on 558 unique traits, we provide an extensive overview of pleiotropy and genetic architecture. We show that trait associated loci cover more than half of the genome, and 90% of those loci are associated with multiple trait domains. We further show that potential causal genetic variants are enriched in coding and flanking regions, as well as in regulatory elements, and how trait-polygenicity is related to an estimate of the required sample size to detect 90% of causal genetic variants. Our results provide novel insights into how genetic variation contributes to trait variation. All GWAS results can be queried and visualized at the GWAS ATLAS resource (http://atlas.ctglab.nl).

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