Understanding and using quantitative genetic variation

Quantitative genetics, or the genetics of complex traits, is the study of those characters which are not affected by the action of just a few major genes. Its basis is in statistical models and methodology, albeit based on many strong assumptions. While these are formally unrealistic, methods work. Analyses using dense molecular markers are greatly increasing information about the architecture of these traits, but while some genes of large effect are found, even many dozens of genes do not explain all the variation. Hence, new methods of prediction of merit in breeding programmes are again based on essentially numerical methods, but incorporating genomic information. Long-term selection responses are revealed in laboratory selection experiments, and prospects for continued genetic improvement are high. There is extensive genetic variation in natural populations, but better estimates of covariances among multiple traits and their relation to fitness are needed. Methods based on summary statistics and predictions rather than at the individual gene level seem likely to prevail for some time yet.

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Technical considerations when designing a gene expression panel for renal transplant diagnosis

Scientific Reports ◽

10.1038/s41598-020-74794-3 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

F. Toulza ◽

K. Dominy ◽

T. Cook ◽

J. Galliford ◽

J. Beadle ◽

...

Keyword(s):

Gene Expression ◽

Renal Transplant ◽

Biological Significance ◽

Tissue Sampling ◽

Individual Gene ◽

Antibody Mediated Rejection ◽

Gene Level ◽

Diagnostic Panel ◽

The Individual ◽

Gene Panels

Abstract Gene expression analysis is emerging as a new diagnostic tool in transplant pathology, in particular for the diagnosis of antibody-mediated rejection. Diagnostic gene expression panels are defined on the basis of their pathophysiological relevance, but also need to be tested for their robustness across different preservatives and analysis platforms. The aim of this study is the investigate the effect of tissue sampling and preservation on candidate genes included in a renal transplant diagnostic panel. Using the NanoString platform, we compared the expression of 219 genes in 51 samples, split for formalin-fixation and paraffin-embedding (FFPE) and RNAlater preservation (RNAlater). We found that overall, gene expression significantly correlated between FFPE and RNAlater samples. However, at the individual gene level, 46 of the 219 genes did not correlate across the 51 matched FFPE and RNAlater samples. Comparing gene expression results using NanoString and qRT-PCR for 18 genes in the same pool of RNA (RNAlater), we found a significant correlation in 17/18 genes. Our study indicates that, in samples from the same routine diagnostic renal transplant biopsy procedure split for FFPE and RNAlater, 21% of 219 genes of potential biological significance do not correlate in expression. Whether this is due to fixatives or tissue sampling, selection of gene panels for routine diagnosis should take this information into consideration.

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Deep transcriptomic profiling reveals the similarity between endothelial cells cultured under static and oscillatory shear stress conditions

Physiological Genomics ◽

10.1152/physiolgenomics.00025.2016 ◽

2016 ◽

Vol 48 (9) ◽

pp. 660-666 ◽

Cited By ~ 15

Author(s):

Congzhen Qiao ◽

Fan Meng ◽

Inhwan Jang ◽

Hanjoong Jo ◽

Y. Eugene Chen ◽

...

Keyword(s):

Endothelial Cells ◽

Shear Stress ◽

Endothelial Function ◽

Stress Conditions ◽

Individual Gene ◽

Gene Level ◽

The Individual ◽

Oscillatory Shear Stress ◽

Whole Transcriptome ◽

Transcriptome Level

Atherosclerosis is a multifactorial disease that preferentially develops in specific regions in the arterial tree. This characteristic is mainly attributed to the unique pattern of hemodynamic shear stress in vivo. High laminar shear stress (LS) found in straight lumen exerts athero-protective effects. Low or oscillatory shear stress (OS) present in regions of lesser curvature and arterial bifurcations predisposes arterial intima to atherosclerosis. Shear stress-regulated endothelial function plays an important role in the process of atherosclerosis. Most in vitro research studies focusing on the molecular mechanisms of endothelial function are performed in endothelial cells (ECs) under cultured static (ST) condition. Some findings, however, are not recapitulated in subsequent translational studies, mostly likely due to the missing biomechanical milieu. Here, we profiled the whole transcriptome of primary human coronary arterial endothelial cells (HCAECs) under different shear stress conditions with RNA sequencing. Among 16,313 well-expressed genes, we detected 8,177 that were differentially expressed in OS vs. LS conditions and 9,369 in ST vs. LS conditions. Notably, only 1,618 were differentially expressed in OS vs. ST conditions. Hierarchical clustering of ECs demonstrated a strong similarity between ECs under OS and ST conditions at the transcriptome level. Subsequent pairwise heat mapping and principal component analysis gave further weight to the similarity. At the individual gene level, expressional analysis of representative well-known genes as well as novel genes showed a comparable amount at mRNA and protein levels in ECs under ST and OS conditions. In conclusion, the present work compared the whole transcriptome of HCAECs under different shear stress conditions at the transcriptome level as well as at the individual gene level. We found that cultured ECs are significantly different from those under LS conditions. Thus using cells under ST conditions is unlikely to elucidate endothelial physiology. Given the revealed high similarities of the endothelial transcriptome under OS and ST conditions, it may be helpful to understand the underlying mechanisms of OS-induced endothelial dysfunction from static cultured endothelial studies.

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The good, the bad, and the ugly: Evolutionary and pathological aspects of gene dosage alterations

PLoS Genetics ◽

10.1371/journal.pgen.1009906 ◽

2021 ◽

Vol 17 (12) ◽

pp. e1009906

Author(s):

M. Felicia Basilicata ◽

Claudia Isabelle Keller Valsecchi

Keyword(s):

Developmental Disorders ◽

Common Ground ◽

Gene Dosage ◽

Paternal Genome ◽

Individual Gene ◽

Developmental Progression ◽

Gene Level ◽

Heteromorphic Sex Chromosomes ◽

Genetic Perturbations ◽

The Individual

Diploid organisms contain a maternal and a paternal genome complement that is thought to provide robustness and allow developmental progression despite genetic perturbations that occur in heterozygosity. However, changes affecting gene dosage from the chromosome down to the individual gene level possess a significant pathological potential and can lead to developmental disorders (DDs). This indicates that expression from a balanced gene complement is highly relevant for proper cellular and organismal function in eukaryotes. Paradoxically, gene and whole chromosome duplications are a principal driver of evolution, while heteromorphic sex chromosomes (XY and ZW) are naturally occurring aneuploidies important for sex determination. Here, we provide an overview of the biology of gene dosage at the crossroads between evolutionary benefit and pathogenicity during disease. We describe the buffering mechanisms and cellular responses to alterations, which could provide a common ground for the understanding of DDs caused by copy number alterations.

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Perturbations of Ribosomal Protein Expression Reveal Overlapping Gene Networks between Drosophila Minutes and Human Cancer

10.1101/2020.12.11.420604 ◽

2020 ◽

Author(s):

Jai A Denton ◽

Mariana Velasque ◽

Floyd A Reed

Keyword(s):

Ribosomal Proteins ◽

Gene Networks ◽

Ribosome Biogenesis ◽

Human Cancer ◽

Whole Body ◽

Individual Gene ◽

Gene Level ◽

The Individual ◽

Time Specific

AbstractRibosomal proteins (RPs) are critical to all cellular operations through their key roles in ribosome biogenesis and translation, as well as their extra-ribosomal functions. Although highly tissue- and time-specific in expression, little is known about the macro-level roles of RPs in shaping transcriptomes. A wealth of RP mutants exist, including the Drosophila melanogaster Minutes, with RP encoding genes that vary from greatly under-expressed to greatly over-expressed. Leveraging a subset of these mutants and using whole-body RNA sequencing, we identified the RP macro transcriptome and then sought to compare it with transcriptomes of pathologies associated with failures of ribosomal function. Gene-based analysis revealed highly variable transcriptomes of RP mutations with little overlap in genes that were differentially expressed. In contrast, weighted gene co-expression network analysis (WGCNA) revealed a highly conserved pattern across all RP mutants studied. When we compared network changes in RP mutants, we observed similarities to transcriptome alterations in human cancer, and thus confirming the oncogenic role of RPs. Therefore, what may appear stochastic at the individual gene level, forms clearly predictable patterns when viewed as a whole.

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MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors

10.1101/2020.06.09.143172 ◽

2020 ◽

Author(s):

Justin Williams ◽

Beisi Xu ◽

Daniel Putnam ◽

Andrew Thrasher ◽

Chunliang Li ◽

...

Keyword(s):

Promoter Activity ◽

Malignant Neoplasms ◽

Clinical Value ◽

Individual Gene ◽

Learning Framework ◽

Genome Wide ◽

Gene Level ◽

Biological Impacts ◽

The Individual ◽

Methylation Patterns

AbstractAlthough genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities (H3K4me3 and H3K27ac enrichment) from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

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Loss of genetic variation in Greek hatchery populations of the European sea bass (Dicentrarchus labrax L.) as revealed by microsatellite DNA analysis

Mediterranean Marine Science ◽

10.12681/mms.1033 ◽

2014 ◽

Vol 16 (1) ◽

pp. 197 ◽

Cited By ~ 6

Author(s):

D. LOUKOVITIS ◽

B. IOANNIDI ◽

D. CHATZIPLIS ◽

G. KOTOULAS ◽

A. MAGOULAS ◽

...

Keyword(s):

Genetic Variation ◽

Microsatellite Dna ◽

Dna Analysis ◽

Natural Populations ◽

Dicentrarchus Labrax ◽

Sea Bass ◽

European Sea Bass ◽

Allele Number ◽

In The Wild ◽

Breeding Programmes

Genetic variation in four reared stocks of European sea bass Dicentrarchus labrax L., originating from Greek commercial farms, was assessed using five polymorphic microsatellite markers and was compared with that of three natural populations from Greece and France. The total number of alleles per marker ranged from 8 to 22 alleles, and hatchery samples showed the same levels of observed heterozygosity with samples from the wild but substantially smaller allelic richness and expected heterozygosity. The genetic differentiation of cultivated samples between them as well as from the wild origin fish was significant as indicated by Fst analysis. All population pairwise comparisons were statistically significant, except for the pair of the two natural Greek populations. Results of microsatellite DNA analysis herein showed a 37 % reduction of the mean allele number in the hatchery samples compared to the wild ones, suggesting random genetic drift and inbreeding events operating in the hatcheries. Knowledge of the genetic variation in D. labrax cultured populations compared with that in the wild ones is essential for setting up appropriate guidelines for proper monitoring and management of the stocks either under traditional practices or for the implementation of selective breeding programmes.

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Integrating Predicted Transcriptome From Multiple Tissues Improves Association Detection

10.1101/292649 ◽

2018 ◽

Cited By ~ 2

Author(s):

Alvaro N. Barbeira ◽

Milton D. Pividori ◽

Jiamao Zheng ◽

Heather E. Wheeler ◽

Dan L. Nicolae ◽

...

Keyword(s):

Complex Traits ◽

Target Genes ◽

Association Studies ◽

Test Methods ◽

Genome Wide Association Studies ◽

Individual Level ◽

Genome Wide ◽

Gene Level ◽

The Individual ◽

The Uk

AbstractIntegration of genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) studies is needed to improve our understanding of the biological mechanisms underlying GWAS hits, and our ability to identify therapeutic targets. Gene-level association test methods such as PrediXcan can prioritize candidate targets. However, limited eQTL sample sizes and absence of relevant developmental and disease context restricts our ability to detect associations. Here we propose an efficient statistical method that leverages the substantial sharing of eQTLs across tissues and contexts to improve our ability to identify potential target genes: MulTiXcan. MulTiXcan integrates evidence across multiple panels while taking into account their correlation. We apply our method to a broad set of complex traits available from the UK Biobank and show that we can detect a larger set of significantly associated genes than using each panel separately. To improve applicability, we developed an extension to work on summary statistics: S-MulTiXcan, which we show yields highly concordant results with the individual level version. Results from our analysis as well as software and necessary resources to apply our method are publicly available.

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Genetic variation in natural populations of Hordeum brevisubulatum native to the Songnen Prairie in northeastern China: Comparison of four nuclear DNA markers

Canadian Journal of Plant Science ◽

10.4141/cjps07029 ◽

2007 ◽

Vol 87 (4) ◽

pp. 773-780 ◽

Cited By ~ 1

Author(s):

Mu Li ◽

Wanli Guo ◽

Lanjuan Hu ◽

Xiaoming Liu ◽

Yufei Zhang ◽

...

Keyword(s):

Genetic Variation ◽

Nuclear Dna ◽

Natural Populations ◽

Similarity Coefficient ◽

Northeastern China ◽

Nuclear Dna Markers ◽

The Individual ◽

Genomic Regions ◽

Hordeum Brevisubulatum ◽

Issr Primers

Hordeum brevisubulatum (Trin) Link, a perennial wild grass, shows high tolerance to salinity- and/or alkaline-eroded soil, and is an important forage grass. Nonetheless, the genetic variation within and among natural populations of this species has not been investigated. In this study, four PCR-based dominant nuclear DNA markers, i.e., amplified fragment length polymorphism (AFLP), inter-simple sequence repeat (ISSR), retrotransposon-microsatellite-amplifiedpolymorphism (REMAP), and random amplified polymor phic DNA (RAPD) were used to investigate the genetic variation of a total of 80 plants with an average of 20 individual plants randomly collected from each of the four natural populations of H. brevisubulatum distributed in the Songnen Prairie in northeastern China. Results indicated that all four markers detected a surprisingly high level of genetic variation among the individual genotypes both within and among populations. Specifically, (i) of the 708 bands produced by 10 AFLP primer pairs, 223 (32%) were polymorphic, corresponding to a genetic similarity coefficient (Dice) range of 0.703 to 0.895 with a mean of 0.793; (ii) of the 174 bands produced by 12 ISSR primers, 149 (85%) were polymorphic, corresponding to a genetic similarity coefficient range of 0.524 to 0.826 with a mean of 0.676; (iii) of the 104 bands produced by REMAP (one retrotransopon-specific primer in combination with each of 8 ISSR primers), 89 (85%) were polymorphic, leading to an average similarity coefficient range of 0.494–0.840 with a mean of 0.688, and; (iv) of the 150 bands produced by 17 RAPD primers, 117 (77%) were polymorphic, giving a similarity coefficient range of 0.526–0.909 with a mean of 0.713. Thus, all four markers are highly informative in detecting genetic variations among the individual genotypes in natural populations of H. brevisubulatum. Nevertheless, no correlation was detected among the markers, suggesting that they likely targeted to different genomic regions of H. brevisubulatum. Whereas ISSR, REMAP and RAPD showed significantly higher levels of polymorphism than AFLP, only the latter was capable of grouping some of the plants largely in accordance with their geographic localities, suggesting population differentiation probably occurred preferentially at genomic regions targeted to by AFLP primers. Key words: Genetic diversity, Hordeum brevisubulatum, Molecular markers, Population differentiation

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MethylationToActivity: a deep-learning framework that reveals promoter activity landscapes from DNA methylomes in individual tumors

Genome Biology ◽

10.1186/s13059-020-02220-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Justin Williams ◽

Beisi Xu ◽

Daniel Putnam ◽

Andrew Thrasher ◽

Chunliang Li ◽

...

Keyword(s):

Promoter Activity ◽

Malignant Neoplasms ◽

Clinical Value ◽

Individual Gene ◽

Learning Framework ◽

Genome Wide ◽

Gene Level ◽

Biological Impacts ◽

The Individual ◽

Methylation Patterns

AbstractAlthough genome-wide DNA methylomes have demonstrated their clinical value as reliable biomarkers for tumor detection, subtyping, and classification, their direct biological impacts at the individual gene level remain elusive. Here we present MethylationToActivity (M2A), a machine learning framework that uses convolutional neural networks to infer promoter activities based on H3K4me3 and H3K27ac enrichment, from DNA methylation patterns for individual genes. Using publicly available datasets in real-world test scenarios, we demonstrate that M2A is highly accurate and robust in revealing promoter activity landscapes in various pediatric and adult cancers, including both solid and hematologic malignant neoplasms.

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Extensive standing genetic variation from a small number of founders enables rapid adaptation in Daphnia

Nature Communications ◽

10.1038/s41467-021-24581-z ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Anurag Chaturvedi ◽

Jiarui Zhou ◽

Joost A. M. Raeymaekers ◽

Till Czypionka ◽

Luisa Orsini ◽

...

Keyword(s):

Genetic Variation ◽

Rapid Evolution ◽

Natural Populations ◽

Genetic Erosion ◽

Genomic Variation ◽

Whole Genome ◽

Rapid Adaptation ◽

Multiple Traits ◽

Evolutionary Trajectory ◽

Study Population

AbstractWe lack a thorough understanding of the origin and maintenance of standing genetic variation that enables rapid evolutionary responses of natural populations. Whole genome sequencing of a resurrected Daphnia population shows that standing genetic variation in over 500 genes follows an evolutionary trajectory that parallels the pronounced and rapid adaptive evolution of multiple traits in response to predator-driven natural selection and its subsequent relaxation. Genetic variation carried by only five founding individuals from the regional genotype pool is shown to suffice at enabling the observed evolution. Our results provide insight on how natural populations can acquire the genomic variation, through colonization by a few regional genotypes, that fuels rapid evolution in response to strong selection pressures. While these evolutionary responses in our study population involved hundreds of genes, we observed no evidence of genetic erosion.

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