scholarly journals Functional genomic approaches to improve crop plant heat stress tolerance

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 1721 ◽  
Author(s):  
Baljeet Singh ◽  
Neha Salaria ◽  
Kajal Thakur ◽  
Sarvjeet Kukreja ◽  
Shristy Gautam ◽  
...  
Keyword(s):  
Heat Stress ◽  
Stress Tolerance ◽  
Association Studies ◽  
Subtractive Hybridization ◽  
Molecular Networks ◽  
Genome Wide Association Studies ◽  
Functional Genomic ◽  
Genome Wide ◽  
Signalling Network ◽  
Heat Stress Tolerance

Heat stress as a yield limiting issue has become a major threat for food security as global warming progresses. Being sessile, plants cannot avoid heat stress. They respond to heat stress by activating complex molecular networks, such as signal transduction, metabolite production and expressions of heat stress-associated genes. Some plants have developed an intricate signalling network to respond and adapt it. Heat stress tolerance is a polygenic trait, which is regulated by various genes, transcriptional factors, proteins and hormones. Therefore, to improve heat stress tolerance, a sound knowledge of various mechanisms involved in the response to heat stress is required. The classical breeding methods employed to enhance heat stress tolerance has had limited success. In this era of genomics, next generation sequencing techniques, availability of genome sequences and advanced biotechnological tools open several windows of opportunities to improve heat stress tolerance in crop plants. This review discusses the potential of various functional genomic approaches, such as genome wide association studies, microarray, and suppression subtractive hybridization, in the process of discovering novel genes related to heat stress, and their functional validation using both reverse and forward genetic approaches. This review also discusses how these functionally validated genes can be used to improve heat stress tolerance through plant breeding, transgenics and genome editing approaches.

scholarly journals Informing disease modelling with brain-relevant functional genomic annotations

Brain ◽  
2019 ◽  
Vol 142 (12) ◽  
pp. 3694-3712 ◽  
Author(s):  
Regina H Reynolds ◽  
John Hardy ◽  
Mina Ryten ◽  
Sarah A Gagliano Taliun
Keyword(s):  
Genetic Association ◽  
Association Studies ◽  
Therapeutic Targets ◽  
Genome Wide Association ◽  
Disease Modelling ◽  
Genome Wide Association Studies ◽  
Functional Genomic ◽  
Genome Wide ◽  
Neuropsychiatric Diseases ◽  
Association Data

How can we best translate the success of genome-wide association studies for neurological and neuropsychiatric diseases into therapeutic targets? Reynolds et al. critically assess existing brain-relevant functional genomic annotations and the tools available for integrating such annotations with summary-level genetic association data.

scholarly journals Functional genomic characterization of the FTO locus in African Americans

2019 ◽  
Vol 51 (11) ◽  
pp. 517-528 ◽  
Author(s):  
Richard Gill ◽  
George Stratigopoulos ◽  
Joseph H. Lee ◽  
Rudolph L. Leibel
Keyword(s):  
Fine Mapping ◽  
Association Studies ◽  
Haplotype Diversity ◽  
Genome Wide Association Studies ◽  
Functional Genomic ◽  
Nucleotide Polymorphisms ◽  
Atherosclerosis Risk In Communities ◽  
Individual Level ◽  
Genome Wide ◽  
High Level

Background: SNPs in the first intron of the fat mass and obesity-associated ( FTO) gene represent the strongest genome-wide associations with adiposity [body mass index (BMI)]; the molecular basis for these associations is under intense investigation. In European populations, the focus of most genome-wide association studies conducted to date, the single nucleotide polymorphisms (SNPs) have indistinguishable associations due to the high level of linkage disequilibrium (LD). However, in African American (AA) individuals, reduced LD and increased haplotype diversity permit finer distinctions among obesity-associated SNPs. Such distinctions are important to mechanistic inferences and for selection of disease SNPs relevant to specific populations. Methods: To identify specific FTO SNP(s) directly related to adiposity, we performed: 1) haplotype analyses of individual-level data in 3,335 AAs from the Atherosclerosis Risk in Communities Cohort (ARIC) study; as well as 2) statistical fine-mapping using summary statistics from a study of FTO in over 20 000 AAs and over 1000 functional genomic annotations. Results: Our haplotype analyses suggest that in AAs at least two distinct signals underlie the intron 1 FTO-adiposity signal. Fine mapping showed that two SNPs have the highest posterior probability of association (PPA) with BMI: rs9927317 (PPA = 0.94) and rs62033405 (PPA = 0.99). These variants overlap possible enhancer sites and the 5′-regions of transcribed genes in the substantia nigra, chondrocytes, and white adipocytes. Conclusions: We found two SNPs in FTO with the highest probability of direct association with BMI in AAs, as well as tissue-specific mechanisms by which these variants may contribute to the pathogenesis of obesity.

17 Genome-wide Association Study for Heat Stress Tolerance in Swine Using Weighted Single-step GBLUP

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 8-8
Author(s):  
Gabriella R Dodd ◽  
Breno O Fragomeni ◽  
Kent A Gray ◽  
Yijian Huang
Keyword(s):  
Heat Stress ◽  
Association Study ◽  
Stress Tolerance ◽  
Genetic Correlation ◽  
Genome Wide Association Study ◽  
Single Step ◽  
Genome Wide Association ◽  
Genome Wide ◽  
Heat Stress Tolerance ◽  
Genomic Regions

Abstract The purpose of this study was to perform a genome-wide association study to determine the genomic regions associated with heat stress tolerance in swine as well as analyze the accuracy of prediction. Phenotypic information on carcass weight was available for 227,043 individuals from commercial farms in North Carolina and Missouri. Individuals were a commercial cross of a Duroc sire and a dam resulting from a Landrace and Large White cross. Genotypic information was available for 8,232 animals with 33,581 SNP. The pedigree file contained 553,448 animals. A 78 on the Temperature Humidity Index (THI) was used as a threshold for heat stress. A two-trait analysis was used with the phenotypes heat stress (trait one) and non-heat stress (trait two). Variance components were calculated via AIREML and breeding values were calculated using single step GBLUP (ssGBLUP). The heritability for trait one and two were calculated at 0.25 and 0.20, respectively, and the genetic correlation was calculated as 0.63. Validation was calculated for 163 genotyped sires with progeny in the last generation. The GEBV of complete data was used as the benchmark, and the accuracy was determined as the correlation between the GEBV of the reduced and complete data for the validation sires. Weighted ssGBLUP did not increase the accuracies, both methods showed a maximum accuracy of 0.32 for trait one and 0.54 for trait two. Manhattan Plots for trait one, trait two, and the difference between the two were created from the results of the two-trait analysis. Windows explaining around 1% of the genetic variance were identified. The only difference between the two traits was a peak at chromosome 14. The genetic correlation suggests different mechanisms for growth under heat stress. The GWAS results show that both traits are highly polygenic, with few genomic regions explaining more than 1% of variance.

scholarly journals Genome-wide association studies for heat stress response in Bos taurus × Bos indicus crossbred cattle

2019 ◽  
Vol 102 (9) ◽  
pp. 8148-8158 ◽  
Author(s):  
Pamela I. Otto ◽  
Simone E.F. Guimarães ◽  
Lucas L. Verardo ◽  
Ana Luísa S. Azevedo ◽  
Jeremie Vandenplas ◽  
...  
Keyword(s):  
Heat Stress ◽  
Stress Response ◽  
Bos Taurus ◽  
Association Studies ◽  
Bos Indicus ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Crossbred Cattle ◽  
Heat Stress Response ◽  
Genome Wide

scholarly journals An Integrative Genomics Approach for Associating Genome-Wide Association Studies Information With Localized and Metastatic Prostate Cancer Phenotypes

2017 ◽  
Vol 12 ◽  
pp. 117727191769581 ◽  
Author(s):  
Chindo Hicks ◽  
Ritika Ramani ◽  
Oliver Sartor ◽  
Ritu Bhalla ◽  
Lucio Miele ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Genetic Susceptibility ◽  
Metastatic Prostate Cancer ◽  
Association Studies ◽  
Biological Pathways ◽  
Genome Wide Association ◽  
Molecular Networks ◽  
Genome Wide Association Studies ◽  
Disease States ◽  
Genome Wide

High-throughput genotyping has enabled discovery of genetic variants associated with an increased risk of developing prostate cancer using genome-wide association studies (GWAS). The goal of this study was to associate GWAS information of patients with primary organ–confined and metastatic prostate cancer using gene expression data and to identify molecular networks and biological pathways enriched for genetic susceptibility variants involved in the 2 disease states. The analysis revealed gene signatures for the 2 disease states and a gene signature distinguishing the 2 patient groups. In addition, the analysis revealed molecular networks and biological pathways enriched for genetic susceptibility variants. The discovered pathways include the androgen, apoptosis, and insulinlike growth factor signaling pathways. This analysis established putative functional bridges between GWAS discoveries and the biological pathways involved in primary organ–confined and metastatic prostate cancer.

scholarly journals Genome-Wide Development and Validation of Cost-Effective KASP Marker Assays for Genetic Dissection of Heat Stress Tolerance in Maize

2020 ◽  
Vol 21 (19) ◽  
pp. 7386
Author(s):  
Ashok Babadev Jagtap ◽  
Yogesh Vikal ◽  
Gurmukh Singh Johal
Keyword(s):  
Heat Stress ◽  
Stress Tolerance ◽  
Cost Effective ◽  
Genetic Dissection ◽  
Rna Seq ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Heat Stress Tolerance ◽  
Kasp Markers

Maize is the third most important cereal crop worldwide. However, its production is vulnerable to heat stress, which is expected to become more and more severe in coming years. Germplasm resilient to heat stress has been identified, but its underlying genetic basis remains poorly understood. Genomic mapping technologies can fill the void, provided robust markers are available to tease apart the genotype-phenotype relationship. In the present investigation, we used data from an RNA-seq experiment to identify single nucleotide polymorphisms (SNPs) between two contrasting lines, LM11 and CML25, sensitive and tolerant to heat stress, respectively. The libraries for RNA-seq were made following heat stress treatment from three separate tissues/organs, comprising the top leaf, ovule, and pollen, all of which are highly vulnerable to damage by heat stress. The single nucleotide variants (SNVs) calling used STAR mapper and GATK caller pipelines in a combined approach to identify highly accurate SNPs between the two lines. A total of 554,423, 410,698, and 596,868 SNVs were discovered between LM11 and CML25 after comparing the transcript sequence reads from the leaf, pollen, and ovule libraries, respectively. Hundreds of these SNPs were then selected to develop into genome-wide Kompetitive Allele-Specific PCR (KASP) markers, which were validated to be robust with a successful SNP conversion rate of 71%. Subsequently, these KASP markers were used to effectively genotype an F2 mapping population derived from a cross of LM11 and CML25. Being highly cost-effective, these KASP markers provide a reliable molecular marker toolkit to not only facilitate the genetic dissection of the trait of heat stress tolerance but also to accelerate the breeding of heat-resilient maize by marker-assisted selection (MAS).

scholarly journals A coding and non-coding transcriptomic perspective on the genomics of human metabolic disease

2018 ◽  
Vol 46 (15) ◽  
pp. 7772-7792 ◽  
Author(s):  
James A Timmons ◽  
Philip J Atherton ◽  
Ola Larsson ◽  
Sanjana Sood ◽  
Ilya O Blokhin ◽  
...  
Keyword(s):  
Metabolic Disease ◽  
Association Studies ◽  
Genomic Structure ◽  
Molecular Networks ◽  
Genome Wide Association Studies ◽  
Catabolic Gene ◽  
Rna Profiling ◽  
Viral Response ◽  
The Core ◽  
Genome Wide

Abstract Genome-wide association studies (GWAS), relying on hundreds of thousands of individuals, have revealed >200 genomic loci linked to metabolic disease (MD). Loss of insulin sensitivity (IS) is a key component of MD and we hypothesized that discovery of a robust IS transcriptome would help reveal the underlying genomic structure of MD. Using 1,012 human skeletal muscle samples, detailed physiology and a tissue-optimized approach for the quantification of coding (>18,000) and non-coding (>15,000) RNA (ncRNA), we identified 332 fasting IS-related genes (CORE-IS). Over 200 had a proven role in the biochemistry of insulin and/or metabolism or were located at GWAS MD loci. Over 50% of the CORE-IS genes responded to clinical treatment; 16 quantitatively tracking changes in IS across four independent studies (P = 0.0000053: negatively: AGL, G0S2, KPNA2, PGM2, RND3 and TSPAN9 and positively: ALDH6A1, DHTKD1, ECHDC3, MCCC1, OARD1, PCYT2, PRRX1, SGCG, SLC43A1 and SMIM8). A network of ncRNA positively related to IS and interacted with RNA coding for viral response proteins (P < 1 × 10−48), while reduced amino acid catabolic gene expression occurred without a change in expression of oxidative-phosphorylation genes. We illustrate that combining in-depth physiological phenotyping with robust RNA profiling methods, identifies molecular networks which are highly consistent with the genetics and biochemistry of human metabolic disease.

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