AIMC Topic: Quantitative Trait Loci

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Leveraging supervised learning for functionally informed fine-mapping of cis-eQTLs identifies an additional 20,913 putative causal eQTLs.

Nature communications Jun 7, 2021
The large majority of variants identified by GWAS are non-coding, motivating detailed characterization of the function of non-coding variants. Experimental methods to assess variants' effect on gene expressions in native chromatin context via direct ...
Humans Adult Gene Expression Profiling Supervised Machine Learning Datasets as Topic Cohort Studies Quantitative Trait Loci Polymorphism, Single Nucleotide Chromosome Mapping Computational Biology
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Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance.

Scientific reports Nov 18, 2020
Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust re...
Chromosome Mapping Genome, Plant Quantitative Trait Loci Genes, Plant Phenotype Genomics Genotype Basidiomycota Disease Resistance Machine Learning Saccharum Plant Diseases
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How Machine Learning Methods Helped Find Putative Rye Wax Genes Among GBS Data.

International journal of molecular sciences Oct 12, 2020
The standard approach to genetic mapping was supplemented by machine learning (ML) to establish the location of the rye gene associated with epicuticular wax formation (glaucous phenotype). Over 180 plants of the biparental F population were genotype...
Genotype Genetic Markers Secale Machine Learning Phenotype Biomarkers Chromosome Mapping Genetics, Population Waxes Quantitative Trait Loci Genes, Plant
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lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.

Scientific data Oct 5, 2020
Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,19...
Humans Phylogeny Molecular Sequence Annotation RNA, Long Noncoding Quantitative Trait Loci Knowledge Bases Organ Specificity
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Sensitivity analysis based on the random forest machine learning algorithm identifies candidate genes for regulation of innate and adaptive immune response of chicken.

Poultry science Sep 12, 2020
Two categories of immune responses-innate and adaptive immunity-have both polygenic backgrounds and a significant environmental component. The goal of the reported study was to define candidate genes and mutations for the immune traits of interest in...
Machine Learning Algorithms Animals Adaptive Immunity Quantitative Trait Loci Chickens Immunity, Innate
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An enhanced machine learning tool for cis-eQTL mapping with regularization and confounder adjustments.

Genetic epidemiology Jul 22, 2020
Many expression quantitative trait loci (eQTL) studies have been conducted to investigate the biological effects of variants in gene regulation. However, these eQTL studies may suffer from low or moderate statistical power and overly conservative fal...
Quantitative Trait Loci Confounding Factors, Epidemiologic Humans Machine Learning Polymorphism, Single Nucleotide Genotype Algorithms Models, Genetic Gene Expression Regulation Phenotype Gene Expression Profiling
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Cross-species regulatory sequence activity prediction.

PLoS computational biology Jul 20, 2020
Machine learning algorithms trained to predict the regulatory activity of nucleic acid sequences have revealed principles of gene regulation and guided genetic variation analysis. While the human genome has been extensively annotated and studied, mod...
Algorithms Genome, Human Mutation Animals Species Specificity Neural Networks, Computer Hepatocytes Mice Quantitative Trait Loci Genetic Variation Machine Learning Humans Epigenomics Gene Expression Regulation Genomics Software Databases, Genetic Models, Genetic Sequence Analysis, DNA Computational Biology Models, Statistical
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Morphological traits of drought tolerant horse gram germplasm: classification through machine learning.

Journal of the science of food and agriculture Jul 3, 2020
BACKGROUND: Horse gram (Macrotyloma uniflorum (Lam.) Verdc.) is an underutilized pulse crop with good drought resistance traits. It is a rich source of protein. Conventional breeding methods for high yielding and abiotic stress tolerant germplasm are...
Quantitative Trait Loci Droughts Plant Breeding Seeds Phenotype Fabaceae Genotype Stress, Physiological Machine Learning Algorithms
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DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning.

PLoS computational biology Feb 3, 2020
Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses...
Quantitative Trait Loci Polymorphism, Single Nucleotide Genetic Association Studies Deep Learning Multivariate Analysis Humans Genome-Wide Association Study
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TSLRF: Two-Stage Algorithm Based on Least Angle Regression and Random Forest in genome-wide association studies.

Scientific reports Dec 2, 2019
One of the most important tasks in genome-wide association analysis (GWAS) is the detection of single-nucleotide polymorphisms (SNPs) which are related to target traits. With the development of sequencing technology, traditional statistical methods a...
Linear Models Polymorphism, Single Nucleotide Machine Learning Arabidopsis Models, Genetic Genome, Plant Genome-Wide Association Study Quantitative Trait Loci Multigene Family Genomics
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