Photosynthesis and heat tolerance of soybean

2018 ◽  
Author(s):  
◽  
Matthew Thomas Herritt
Keyword(s):  
Candidate Genes ◽  
Spectral Reflectance ◽  
Crop Improvement ◽  
Sugar Transport ◽  
Transport Processes ◽  
Photochemical Quenching ◽  
Candidate Snps ◽  
Nucleotide Polymorphisms ◽  
Canopy Spectral Reflectance ◽  
Reflectance Measurements

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] The Photochemical Reflectance Index (PRI) is determined from canopy spectral reflectance measurements and can provide important information about photosynthesis. The PRI can be used to assess the epoxidation state of xanthophyll pigments which provides information on non-photochemical quenching (NPQ) and the amount of energy used for photosynthesis. Genome wide association analyses were conducted to identify Single Nucleotide Polymorphisms (SNPs) and genomic loci associated with PRI using data from a soybean [Glycine max (L.) Merr.] diversity panel grown under field conditions in two years. Based on a mixed linear model, 31 unique candidate SNPs that identify 15 putative loci on 11 chromosomes were identified. Several candidate genes known to be associated with NPQ, photosynthesis, and sugar transport processes were identified in the proximity of 10 putative loci. Violaxanthin de-epoxidase, one of the identified genes, is directly involved in the xanthophyll cycle which plays a major role in NPQ. This study is the first to identify genomic loci for PRI and illustrates the potential of canopy spectral reflectance measurements for high-throughput phenotyping of a photosynthesis related trait. Significant SNPs, candidate genes, and genotypes contrasting for PRI identified in this study may prove useful for crop improvement efforts.

scholarly journals Association Mapping of Total Carotenoids in Diverse Soybean Genotypes Based on Leaf Extracts and High-Throughput Canopy Spectral Reflectance Measurements

PLoS ONE ◽  
2015 ◽  
Vol 10 (9) ◽  
pp. e0137213 ◽  
Author(s):  
Arun Prabhu Dhanapal ◽  
Jeffery D. Ray ◽  
Shardendu K. Singh ◽  
Valerio Hoyos-Villegas ◽  
James R. Smith ◽  
...  
Keyword(s):  
Association Mapping ◽  
High Throughput ◽  
Spectral Reflectance ◽  
Leaf Extracts ◽  
Total Carotenoids ◽  
Soybean Genotypes ◽  
Canopy Spectral Reflectance ◽  
Reflectance Measurements

scholarly journals Integrating GWAS and Transcriptomics to Identify Genes Involved in Seed Dormancy in Rice

2021 ◽  
Author(s):  
Jin Shi ◽  
Jianxin Shi ◽  
Wanqi Liang ◽  
Dabing Zhang
Keyword(s):  
Candidate Genes ◽  
Seed Dormancy ◽  
Genome Wide Association Study ◽  
Crop Improvement ◽  
Heading Date ◽  
Differentially Expressed ◽  
Nucleotide Polymorphisms ◽  
Cultivated Rice ◽  
A Genome ◽  
Seed Harvest

Abstract Seed dormancy is a key agricultural trait to prevent pre-harvest sprouting in crop plants such as rice (Oryza sativa L.), wheat (Triticum aestivum), and barley (Hordeum vulgare L.). However, our knowledge of seed dormancy is hampered by the complexities of studying a trait that changes over time after seed harvest, and is complicated by interactions between phytohormones, other regulators, and the environment. Here, we have conducted a genome-wide association study using a panel of 311 natural accessions of cultivated rice, examining a total of 519,158 single nucleotide polymorphisms (SNPs). Eight quantitative trait loci (QTLs) were found to associate with seed dormancy; expression of candidate genes within 100 kb of each QTL was examined in two published, germination-specific transcriptomic datasets. Ten candidate genes, differentially expressed within the first four days post-imbibition, were identified. Five of these genes had previously been associated with awn length, heading date, yield, and spikelet length phenotypes. In addition, previously identified genes involved in hormone signaling during germination were found to be differentially expressed between a japonica and an indica line; SNPs in the promoter of Os9BGlu33 were associated with germination index. Collectively, our results are useful for future characterization of seed dormancy mechanism and crop improvement, and suggest haplotypes for further analysis that may be of use to boost PHS resistance in rice.

scholarly journals Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 192
Author(s):  
Xinghai Duan ◽  
Bingxing An ◽  
Lili Du ◽  
Tianpeng Chang ◽  
Mang Liang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Curve ◽  
Growth And Development ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Coefficient Of Determination ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

Dementia key gene identification with multi-layered SNP-gene-disease network

2020 ◽  
Vol 36 (Supplement_2) ◽  
pp. i831-i839
Author(s):  
Dong-gi Lee ◽  
Myungjun Kim ◽  
Sang Joon Son ◽  
Chang Hyung Hong ◽  
Hyunjung Shin
Keyword(s):  
Candidate Genes ◽  
Learning Algorithm ◽  
Search Space ◽  
Supplementary Information ◽  
Gene Identification ◽  
Nucleotide Polymorphisms ◽  
Disease Network ◽  
Single Nucleotide ◽  
Key Genes ◽  
Significant Attention

Abstract Motivation Recently, various approaches for diagnosing and treating dementia have received significant attention, especially in identifying key genes that are crucial for dementia. If the mutations of such key genes could be tracked, it would be possible to predict the time of onset of dementia and significantly aid in developing drugs to treat dementia. However, gene finding involves tremendous cost, time and effort. To alleviate these problems, research on utilizing computational biology to decrease the search space of candidate genes is actively conducted. In this study, we propose a framework in which diseases, genes and single-nucleotide polymorphisms are represented by a layered network, and key genes are predicted by a machine learning algorithm. The algorithm utilizes a network-based semi-supervised learning model that can be applied to layered data structures. Results The proposed method was applied to a dataset extracted from public databases related to diseases and genes with data collected from 186 patients. A portion of key genes obtained using the proposed method was verified in silico through PubMed literature, and the remaining genes were left as possible candidate genes. Availability and implementation The code for the framework will be available at http://www.alphaminers.net/. Supplementary information Supplementary data are available at Bioinformatics online.

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

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.

149 Integration of Selection Signatures Analyses and Weighted Single-step GWAS to Prioritize Candidate Genes for Body Conformation Traits in Pigs

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 76-77
Author(s):  
Seyed Milad Vahedi ◽  
Siavash Salek Ardestani ◽  
Duy Ngoc Do ◽  
Karim Karimi ◽  
Younes Miar
Keyword(s):  
Candidate Genes ◽  
Complex Traits ◽  
Body Height ◽  
Single Step ◽  
Fixation Index ◽  
Nucleotide Polymorphisms ◽  
Selection Signatures ◽  
Body Conformation ◽  
Yorkshire Pigs ◽  
Estimated Breeding Values

Abstract Body conformation traits such as body height (BH) and body length (BL) have been included in the swine industry’s selection criteria. The objective of this study was to identify the quantitative trait loci (QTLs) and candidate genes for pig conformation traits using an integration of selection signatures analyses and weighted single-step GWAS (WssGWAS). Body measurement records of 5,593 Yorkshire pigs of which 598 animals were genotyped with Illumina 50K panel were used. Estimated breeding values (EBVs) for BH and BL were computed using univariate animal models. Genotyped animals were grouped into top 5% and bottom 5% based on their EBVs, and selection signatures analyses were performed using fixation index (Fst), FLK, hapFLK, and Rsb statistics, which were then combined as a Mahalanobis distance (Md) framework. The WssGWAS was conducted to detect the single nucleotide polymorphisms (SNPs) associated with the studied traits. The top 1% SNPs (n=530) from Md distribution that overlapped with the top 1% SNPs from WssGWAS (n = 530) were used to detect the candidate genes. A total of 31 and six overlapped SNPs were found to be associated with BH and BL, respectively. Several candidate genes were identified for BH (PARVA, DCDC1, SYT1, CASTOR2, RGSL1, RGS8, RBMS3, TGFBR2, and HS6ST1) and BL (SNTB1, AK7, PAPOLA, KSR1, CHODL, and BMP2), explaining 2.58% and 0.42% of the trait’s genetic variation, respectively. Our results indicated that integrating data from the signatures of selection tests with WssGWAS could help elucidate genomic regions underlying complex traits.

Variants in the VCAM1 gene and risk for symptomatic stroke in sickle cell disease

Blood ◽  
2002 ◽  
Vol 100 (13) ◽  
pp. 4303-4309 ◽  
Author(s):  
James G. Taylor VI ◽  
Delia C. Tang ◽  
Sharon A. Savage ◽  
Susan F. Leitman ◽  
Seth I. Heller ◽  
...  
Keyword(s):  
Sickle Cell ◽  
Critical Role ◽  
Genome Project ◽  
Monogenic Disease ◽  
Candidate Snps ◽  
Healthy Population ◽  
Nucleotide Polymorphisms ◽  
Coding Region ◽  
A Cell ◽  
The Human Genome Project

Stroke is a major cause of morbidity and mortality in sickle cell (SS) disease. Genetic risk factors have been postulated to contribute to this clinical outcome. The human genome project has substantially increased the catalog of variations in genes, many of which could modify the risk for manifestations of disease outcome in a monogenic disease, namely SS. VCAM1 is a cell adhesion molecule postulated to play a critical role in the pathogenesis of SS disease. We identified a total of 33 single nucleotide polymorphisms (SNPs) by sequencing the entire coding region, 2134 bp upstream of the 5′ end of the published cDNA, 217 bp downstream of the 3′ end of the cDNA, and selected intronic regions of the VCAM1 locus. Allelic frequencies for selected SNPs were determined in a healthy population. We subsequently analyzed 4 nonsynonymous coding, 2 synonymous coding, and 4 common promoter SNPs in a genetic association study of clinically apparent stroke in SS disease conducted in a cohort derived from a single institution in Jamaica (51 symptomatic cases and 51 matched controls). Of the 10 candidate SNPs analyzed in this pilot study, the variant allele of the nonsynonymous SNP, VCAM1 G1238C, may be associated with protection from stroke (odds ratio [OR] 0.35, 95% confidence interval [CI] 0.15-0.83, P = .04). Further study is required to confirm the importance of this variant inVCAM1 as a clinically useful modifier of outcome in SS disease.

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