scholarly journals Prospects for Molecular Breeding in Cotton, Gossypium spp

2020 ◽  
Author(s):  
Ishwarappa S. Katageri ◽  
S. Anjan Gowda ◽  
Prashanth B.N ◽  
Mahesh Biradar ◽  
Rajeev M ◽  
...  
Keyword(s):  
Molecular Biology ◽  
Genetic Engineering ◽  
Genomic Selection ◽  
Fine Mapping ◽  
Association Studies ◽  
Fiber Quality ◽  
High Time ◽  
Cotton Production ◽  
Minor Qtls ◽  
Reference Genomes

Conventional breeding interventions in cotton have been successful and these techniques have doubled the productivity of cotton, but it took around 40 years. One of the techniques of molecular biology i.e., genetic engineering has brought significant improvement in productivity within the year of introduction. With cotton genomics maturing, many reference genomes and related genomic resources have been developed. Newer wild species have been discovered and many countries are conserving genetic resources within and between species. This valuable germplasm can be exchanged among countries for increasing cotton productivity. As many as 249 Mapping and Association studies have been carried out and many QTLs have been discovered and it is high time for researchers to get into fine-mapping studies. Techniques of genomic selection hold valuable trust for deciphering quantitative traits like fiber quality and productivity since they take in to account all minor QTLs. There are just two studies involving genomic selection in cotton, underlining its huge prospects in cotton research. Genome editing and transformation techniques have been widely used in cotton with as many as 65 events being developed across various characters, and eight studies carried out using crisper technology. These promising technologies have huge prospects for cotton production sustainability.

scholarly journals CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

2019 ◽  
Author(s):  
Jianhua Wang ◽  
Dandan Huang ◽  
Yao Zhou ◽  
Hongcheng Yao ◽  
Huanhuan Liu ◽  
...  
Keyword(s):  
Fine Mapping ◽  
Genetic Variants ◽  
Association Studies ◽  
Complex Trait ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Genome Wide ◽  
Credible Sets ◽  
Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

Mulches and Nitrogen Application Improves Cotton Yield and Fiber Quality

2019 ◽  
Vol 1 (1) ◽  
pp. 09-13
Author(s):  
Hakoomat Ali ◽  
Asad Abbas ◽  
Shabir Hussain ◽  
Shoukat Ali Abid ◽  
Shazia Khaliq ◽  
...  
Keyword(s):  
Wheat Straw ◽  
Crop Residues ◽  
Fiber Quality ◽  
Fertilizer Application ◽  
Cotton Yield ◽  
Nitrogen Application ◽  
Cotton Production ◽  
Nitrogen Levels ◽  
Important Cash Crop ◽  
Wheat Straw Mulch

Cotton is an important cash crop and source of foreign exchange. Nitrogen is a critical nutrient for plant growth throughout the life span of the crop. Wheat straw mulch not only source of nitrogen supply but also improves soil fertility and reduces soil erosion. The current study was performed to investigate the effects of mulches and nitrogen application on cotton productivity and fiber quality at the Central Cotton Research Institute (CCRI), Multan. Two crop residues i.e. wheat straw and non wheat straw were used in main plots while nitrogen levels viz. 0,50, 100 and 150 kg ha-1 were randomized in subplots. The highest seed cotton yield (22.99 t ha-1) was obtained by the combination of nitrogen fertilizer application highest level (150 kg N ha-1) along with the wheat straw (20.27 t ha-1). The fiber quality was also affected by the wheat straw along with nitrogen application 150 kg N ha-1 and gave maximum results. In conclusion, wheat straw along with 150 kg ha-1 of Nitrogen application gave maximum results on cotton production as compared to non straw with low nitrogen application.

Molecular biology of mosquito vitellogenesis: from basic studies to genetic engineering of antipathogen immunity

2002 ◽  
Vol 32 (10) ◽  
pp. 1275-1286 ◽  
Author(s):  
Alexander S. Raikhel ◽  
Vladimir A. Kokoza ◽  
Jinsong Zhu ◽  
David Martin ◽  
Sheng-Fu Wang ◽  
...  
Keyword(s):  
Molecular Biology ◽  
Genetic Engineering ◽  
Basic Studies

WHEAT PROTEIN MOLECULAR BIOLOGY AND GENETIC ENGINEERING: IMPLICATIONS FOR QUALITY IMPROVEMENT

1995 ◽  
pp. 199-205
Author(s):  
P.R. Shewry ◽  
A.S. Tatham ◽  
J. Greenfield ◽  
N.G. Halford ◽  
S. Thompson ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Molecular Biology ◽  
Genetic Engineering ◽  
Wheat Protein

scholarly journals Fine mapping of breast cancer genome-wide association studies loci in women of African ancestry identifies novel susceptibility markers

2013 ◽  
Vol 34 (7) ◽  
pp. 1520-1528 ◽  
Author(s):  
Y. Zheng ◽  
T. O. Ogundiran ◽  
A. G. Falusi ◽  
K. L. Nathanson ◽  
E. M. John ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Fine Mapping ◽  
Association Studies ◽  
African Ancestry ◽  
Cancer Genome ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide

scholarly journals Historical Datasets Support Genomic Selection Models for the Prediction of Cotton Fiber Quality Phenotypes Across Multiple Environments

2018 ◽  
Vol 8 (5) ◽  
pp. 1721-1732 ◽  
Author(s):  
Washington Gapare ◽  
Shiming Liu ◽  
Warren Conaty ◽  
Qian-Hao Zhu ◽  
Vanessa Gillespie ◽  
...  
Keyword(s):  
Genomic Selection ◽  
Cotton Fiber ◽  
Fiber Quality ◽  
Selection Models ◽  
Cotton Fiber Quality ◽  
Multiple Environments

Identification of ST3AGL4, MFHAS1, CSNK2A2 and CD226 as loci associated with systemic lupus erythematosus (SLE) and evaluation of SLE genetics in drug repositioning

2018 ◽  
Vol 77 (7) ◽  
pp. 1078-1084 ◽  
Author(s):  
Yong-Fei Wang ◽  
Yan Zhang ◽  
Zhengwei Zhu ◽  
Ting-You Wang ◽  
David L Morris ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Fine Mapping ◽  
Lupus Erythematosus ◽  
Drug Repositioning ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Systemic Lupus ◽  
Genome Wide ◽  
Causal Variants

ObjectivesSystemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic component in its pathogenesis. Through genome-wide association studies (GWAS), we recently identified 10 novel loci associated with SLE and uncovered a number of suggestive loci requiring further validation. This study aimed to validate those loci in independent cohorts and evaluate the role of SLE genetics in drug repositioning.MethodsWe conducted GWAS and replication studies involving 12 280 SLE cases and 18 828 controls, and performed fine-mapping analyses to identify likely causal variants within the newly identified loci. We further scanned drug target databases to evaluate the role of SLE genetics in drug repositioning.ResultsWe identified three novel loci that surpassed genome-wide significance, including ST3AGL4 (rs13238909, pmeta=4.40E-08), MFHAS1 (rs2428, pmeta=1.17E-08) and CSNK2A2 (rs2731783, pmeta=1.08E-09). We also confirmed the association of CD226 locus with SLE (rs763361, pmeta=2.45E-08). Fine-mapping and functional analyses indicated that the putative causal variants in CSNK2A2 locus reside in an enhancer and are associated with expression of CSNK2A2 in B-lymphocytes, suggesting a potential mechanism of association. In addition, we demonstrated that SLE risk genes were more likely to be interacting proteins with targets of approved SLE drugs (OR=2.41, p=1.50E-03) which supports the role of genetic studies to repurpose drugs approved for other diseases for the treatment of SLE.ConclusionThis study identified three novel loci associated with SLE and demonstrated the role of SLE GWAS findings in drug repositioning.

scholarly journals Intrinsic DNA topology as a prioritization metric in genomic fine-mapping studies

2020 ◽  
Vol 48 (20) ◽  
pp. 11304-11321
Author(s):  
Hannah C Ainsworth ◽  
Timothy D Howard ◽  
Carl D Langefeld
Keyword(s):  
Fine Mapping ◽  
Lupus Erythematosus ◽  
Association Studies ◽  
Prediction Method ◽  
Dna Topology ◽  
Genomic Region ◽  
Skewed Distribution ◽  
Functional Polymorphisms ◽  
Coding Regions ◽  
Sequence Dependent

Abstract In genomic fine-mapping studies, some approaches leverage annotation data to prioritize likely functional polymorphisms. However, existing annotation resources can present challenges as many lack information for novel variants and/or may be uninformative for non-coding regions. We propose a novel annotation source, sequence-dependent DNA topology, as a prioritization metric for fine-mapping. DNA topology and function are well-intertwined, and as an intrinsic DNA property, it is readily applicable to any genomic region. Here, we constructed and applied Minor Groove Width (MGW) as a prioritization metric. Using an established MGW-prediction method, we generated a MGW census for 199 038 197 SNPs across the human genome. Summarizing a SNP’s change in MGW (ΔMGW) as a Euclidean distance, ΔMGW exhibited a strongly right-skewed distribution, highlighting the infrequency of SNPs that generate dissimilar shape profiles. We hypothesized that phenotypically-associated SNPs can be prioritized by ΔMGW. We tested this hypothesis in 116 regions analyzed by a Massively Parallel Reporter Assay and observed enrichment of large ΔMGW for functional polymorphisms (P = 0.0007). To illustrate application in fine-mapping studies, we applied our MGW-prioritization approach to three non-coding regions associated with systemic lupus erythematosus. Together, this study presents the first usage of sequence-dependent DNA topology as a prioritization metric in genomic association studies.

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