Relevant bibliographies by topics / Complex traits

Academic literature on the topic 'Complex traits'

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Published: 4 June 2021
Last updated: 31 August 2024

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Journal articles on the topic "Complex traits"

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Gurwitz, D. "Complex traits, complex answers." Molecular Psychiatry 2, no. 2 (March 1997): 89–90. http://dx.doi.org/10.1038/sj.mp.4000255.

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Swami, Meera. "Networking complex traits." Nature Reviews Genetics 10, no. 4 (April 2009): 219. http://dx.doi.org/10.1038/nrg2566.

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Gjessing, Håkon K., and Rolv Terje Lie. "Biometrical modelling in genetics: are complex traits too complex?" Statistical Methods in Medical Research 17, no. 1 (February 2008): 75–96. http://dx.doi.org/10.1177/0962280207081241.

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The field of traditional biometrical genetics uses mixed-effects models to quantify the influence of genetic and environmental factors on a biological trait, based essentially on estimating within-family trait correlations. Such analyses provide a useful preview of what may be discovered with the emerging full-scale genotyping strategies. However, biometrical analyses require unrealistically large sample sizes to obtain a reasonable precision, particularly for dichotomous traits. In addition, it may be very difficult to separate genetic and environmental effects because environmental correlations are poorly understood. We illustrate these and other difficulties using population-based cousins and nuclear family data for birth weight, collected from the Medical Birth Registry of Norway.
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Skelly, Daniel A., Narayanan Raghupathy, Raymond F. Robledo, Joel H. Graber, and Elissa J. Chesler. "Reference Trait Analysis Reveals Correlations Between Gene Expression and Quantitative Traits in Disjoint Samples." Genetics 212, no. 3 (May 21, 2019): 919–29. http://dx.doi.org/10.1534/genetics.118.301865.

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Systems genetic analysis of complex traits involves the integrated analysis of genetic, genomic, and disease-related measures. However, these data are often collected separately across multiple study populations, rendering direct correlation of molecular features to complex traits impossible. Recent transcriptome-wide association studies (TWAS) have harnessed gene expression quantitative trait loci (eQTL) to associate unmeasured gene expression with a complex trait in genotyped individuals, but this approach relies primarily on strong eQTL. We propose a simple and powerful alternative strategy for correlating independently obtained sets of complex traits and molecular features. In contrast to TWAS, our approach gains precision by correlating complex traits through a common set of continuous phenotypes instead of genetic predictors, and can identify transcript–trait correlations for which the regulation is not genetic. In our approach, a set of multiple quantitative “reference” traits is measured across all individuals, while measures of the complex trait of interest and transcriptional profiles are obtained in disjoint subsamples. A conventional multivariate statistical method, canonical correlation analysis, is used to relate the reference traits and traits of interest to identify gene expression correlates. We evaluate power and sample size requirements of this methodology, as well as performance relative to other methods, via extensive simulation and analysis of a behavioral genetics experiment in 258 Diversity Outbred mice involving two independent sets of anxiety-related behaviors and hippocampal gene expression. After splitting the data set and hiding one set of anxiety-related traits in half the samples, we identified transcripts correlated with the hidden traits using the other set of anxiety-related traits and exploiting the highest canonical correlation (R = 0.69) between the trait data sets. We demonstrate that this approach outperforms TWAS in identifying associated transcripts. Together, these results demonstrate the validity, reliability, and power of reference trait analysis for identifying relations between complex traits and their molecular substrates.
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Phillips, Patrick C. "From complex traits to complex alleles." Trends in Genetics 15, no. 1 (January 1999): 6–8. http://dx.doi.org/10.1016/s0168-9525(98)01622-9.

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Rancelis, Tautvydas, Ingrida Domarkiene, Laima Ambrozaityte, and Algirdas Utkus. "Implementing Core Genes and an Omnigenic Model for Behaviour Traits Prediction in Genomics." Genes 14, no. 8 (August 16, 2023): 1630. http://dx.doi.org/10.3390/genes14081630.

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A high number of genome variants are associated with complex traits, mainly due to genome-wide association studies (GWAS). Using polygenic risk scores (PRSs) is a widely accepted method for calculating an individual’s complex trait prognosis using such data. Unlike monogenic traits, the practical implementation of complex traits by applying this method still falls behind. Calculating PRSs from all GWAS data has limited practical usability in behaviour traits due to statistical noise and the small effect size from a high number of genome variants involved. From a behaviour traits perspective, complex traits are explored using the concept of core genes from an omnigenic model, aiming to employ a simplified calculation version. Simplification may reduce the accuracy compared to a complete PRS encompassing all trait-associated variants. Integrating genome data with datasets from various disciplines, such as IT and psychology, could lead to better complex trait prediction. This review elucidates the significance of clear biological pathways in understanding behaviour traits. Specifically, it highlights the essential role of genes related to hormones, enzymes, and neurotransmitters as robust core genes in shaping these traits. Significant variations in core genes are prominently observed in behaviour traits such as stress response, impulsivity, and substance use.
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Schork, Nicholas J. "Genetically Complex Cardiovascular Traits." Hypertension 29, no. 1 (January 1997): 145–49. http://dx.doi.org/10.1161/01.hyp.29.1.145.

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Womack, James E., Hyun‐Jun Jang, and Mi Ok Lee. "Genomics of complex traits." Annals of the New York Academy of Sciences 1271, no. 1 (October 2012): 33–36. http://dx.doi.org/10.1111/j.1749-6632.2012.06733.x.

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Ofria, Charles, Wei Huang, and Eric Torng. "On the Gradual Evolution of Complexity and the Sudden Emergence of Complex Features." Artificial Life 14, no. 3 (July 2008): 255–63. http://dx.doi.org/10.1162/artl.2008.14.3.14302.

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Evolutionary theory explains the origin of complex organismal features through a combination of reusing and extending information from less-complex traits, and by needing to exploit only one of many unlikely pathways to a viable solution. While the appearance of a new trait may seem sudden, we show that the underlying information associated with each trait evolves gradually. We study this process using digital organisms, self-replicating computer programs that mutate and evolve novel traits, including complex logic operations. When a new complex trait first appears, its proper function immediately requires the coordinated operation of many genomic positions. As the information associated with a trait increases, the probability of its simultaneous introduction drops exponentially, so it is nearly impossible for a significantly complex trait to appear without reusing existing information. We show that the total information stored in the genome increases only marginally when a trait first appears. Furthermore, most of the information associated with a new trait is either correlated with existing traits or co-opted from traits that were lost in conjunction with the appearance of the new trait. Thus, while total genomic information increases incrementally, traits that require much more information can still arise during the evolutionary process.
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Ou, Jen-Hsiang, Tilman Rönneburg, Örjan Carlborg, Christa Ferst Honaker, Paul B. Siegel, and Carl-Johan Rubin. "Complex genetic architecture of the chicken Growth1 QTL region." PLOS ONE 19, no. 5 (May 13, 2024): e0295109. http://dx.doi.org/10.1371/journal.pone.0295109.

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The genetic complexity of polygenic traits represents a captivating and intricate facet of biological inheritance. Unlike Mendelian traits controlled by a single gene, polygenic traits are influenced by multiple genetic loci, each exerting a modest effect on the trait. This cumulative impact of numerous genes, interactions among them, environmental factors, and epigenetic modifications results in a multifaceted architecture of genetic contributions to complex traits. Given the well-characterized genome, diverse traits, and range of genetic resources, chicken (Gallus gallus) was employed as a model organism to dissect the intricate genetic makeup of a previously identified major Quantitative Trait Loci (QTL) for body weight on chromosome 1. A multigenerational advanced intercross line (AIL) of 3215 chickens whose genomes had been sequenced to an average of 0.4x was analyzed using genome-wide association study (GWAS) and variance-heterogeneity GWAS (vGWAS) to identify markers associated with 8-week body weight. Additionally, epistatic interactions were studied using the natural and orthogonal interaction (NOIA) model. Six genetic modules, two from GWAS and four from vGWAS, were strongly associated with the studied trait. We found evidence of both additive- and non-additive interactions between these modules and constructed a putative local epistasis network for the region. Our screens for functional alleles revealed a missense variant in the gene ribonuclease H2 subunit B (RNASEH2B), which has previously been associated with growth-related traits in chickens and Darwin’s finches. In addition, one of the most strongly associated SNPs identified is located in a non-coding region upstream of the long non-coding RNA, ENSGALG00000053256, previously suggested as a candidate gene for regulating chicken body weight. By studying large numbers of individuals from a family material using approaches to capture both additive and non-additive effects, this study advances our understanding of genetic complexities in a highly polygenic trait and has practical implications for poultry breeding and agriculture.
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Dissertations / Theses on the topic "Complex traits"

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Young, Alexander Thomas Ian Strudwick. "Interactions in complex traits." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:4329ac12-00a5-466a-950f-dcb17aaf2e10.

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The availability of cheap genotyping technologies has enabled to collection of very large samples with both genetic and phenotypic information, enabling the interrogation of the genetic architecture of complex traits in humans and other organisms. The role of interactions between genetic variants and between genetic variants and environmental factors in complex traits is not well characterised, especially in humans. This is in part due to a lack of theory and methods designed for powerful investigation of interactions in complex traits in large-scale datasets. This thesis develops both theory and methods relating to interactions between genetic variants and between genetic and environmental factors, complemented by empirical analyses aimed at discovering the influence of interactions on complex traits. The effect of genetic variation on trait variation can be decomposed into components reflecting interactions involving different numbers of genetic variants. The first part of this thesis generalises classical theory on the decomposition of the genetic variance into components arising from different types of interaction to finite populations, where the influence of interactions is more easily detected. The theory is applied to determine the proportion of growth variance from pairwise and third and higher order interactions in a yeast cross. The subsequent parts of the thesis are more directly concerned with interactions between genetic variants and environmental factors. It is first demonstrated that multiple lifestyle factors modify the effect of variants in the FTO gene on body mass index (BMI). This motivates the development of the heteroskedastic linear mixed model (HLMM), which exploits changes in variability with genotype to aid discovery of genetic variants involved in interactions. An efficient algorithm for application of the HLMM to large scale datasets is developed and applied to discover genetic variants likely to be involved in interactions on BMI.
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Bell, Jordana Tzenova. "Epistasis in complex human traits." Thesis, University of Oxford, 2006. http://ora.ox.ac.uk/objects/uuid:547db446-c84c-4a6c-8b5c-ce960f7765c5.

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Hemani, Gibran. "Dissecting genetic interactions in complex traits." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6472.

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Of central importance in the dissection of the components that govern complex traits is understanding the architecture of natural genetic variation. Genetic interaction, or epistasis, constitutes one aspect of this, but epistatic analysis has been largely avoided in genome wide association studies because of statistical and computational difficulties. This thesis explores both issues in the context of two-locus interactions. Initially, through simulation and deterministic calculations it was demonstrated that not only can epistasis maintain deleterious mutations at intermediate frequencies when under selection, but that it may also have a role in the maintenance of additive variance. Based on the epistatic patterns that are evolutionarily persistent, and the frequencies at which they are maintained, it was shown that exhaustive two dimensional search strategies are the most powerful approaches for uncovering both additive variance and the other genetic variance components that are co-precipitated. However, while these simulations demonstrate encouraging statistical benefits, two dimensional searches are often computationally prohibitive, particularly with the marker densities and sample sizes that are typical of genome wide association studies. To address this issue different software implementations were developed to parallelise the two dimensional triangular search grid across various types of high performance computing hardware. Of these, particularly effective was using the massively-multi-core architecture of consumer level graphics cards. While the performance will continue to improve as hardware improves, at the time of testing the speed was 2-3 orders of magnitude faster than CPU based software solutions that are in current use. Not only does this software enable epistatic scans to be performed routinely at minimal cost, but it is now feasible to empirically explore the false discovery rates introduced by the high dimensionality of multiple testing. Through permutation analysis it was shown that the significance threshold for epistatic searches is a function of both marker density and population sample size, and that because of the correlation structure that exists between tests the threshold estimates currently used are overly stringent. Although the relaxed threshold estimates constitute an improvement in the power of two dimensional searches, detection is still most likely limited to relatively large genetic effects. Through direct calculation it was shown that, in contrast to the additive case where the decay of estimated genetic variance was proportional to falling linkage disequilibrium between causal variants and observed markers, for epistasis this decay was exponential. One way to rescue poorly captured causal variants is to parameterise association tests using haplotypes rather than single markers. A novel statistical method that uses a regularised parameter selection procedure on two locus haplotypes was developed, and through extensive simulations it can be shown that it delivers a substantial gain in power over single marker based tests. Ultimately, this thesis seeks to demonstrate that many of the obstacles in epistatic analysis can be ameliorated, and with the current abundance of genomic data gathered by the scientific community direct search may be a viable method to qualify the importance of epistasis.
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Breeze, Charles E. "Epigenetics of complex traits and diseases." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/10038878/.

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Thousands of genetic and epigenetic variants have been identified for many common diseases including cancer through genome-wide association studies (GWAS) and epigenome-wide association studies (EWAS). To advance the complex interpretation of both GWAS and EWAS results, I developed new software tools (FORGE2 and eFORGE) for the analysis and interpretation of GWAS and EWAS data, respectively. Both tools determine the cell type-specific regulatory component of a set of target regions (either GWAS-identified genetic variants or EWAS-identified differentially methylated positions). This is achieved by detecting enrichment of overlap with histone mark peaks or DNase I hypersensitive sites across hundreds of tissues, primary cell types, and cell lines from the ENCODE, Roadmap Epigenomics, and BLUEPRINT projects. Application of both tools to publicly available datasets identified novel disease-relevant cell types for many common diseases, a stem cell-like signature in cancer EWAS, and also demonstrated the ability to detect cell-composition effects for EWAS performed on heterogeneous tissues. To complement these bioinformatics efforts and validate selected variants predicted by FORGE2, eFORGE and additional analyses, I performed conformation capture using 4C-seq to fine-map the 3D context of the genomic regions involved, uncovering novel interactions for autoimmunity-associated variants and IKZF3.
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Allchin, Lorraine Doreen May. "Statistical methods for mapping complex traits." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:65f392ba-1b64-4b00-8871-7cee98809ce1.

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The first section of this thesis addresses the problem of simultaneously identifying multiple loci that are associated with a trait, using a Bayesian Markov Chain Monte Carlo method. It is applicable to both case/control and quantitative data. I present simulations comparing the methods to standard frequentist methods in human case/control and mouse QTL datasets, and show that in the case/control simulations the standard frequentist method out performs my model for all but the highest effect simulations and that for the mouse QTL simulations my method performs as well as the frequentist method in some cases and worse in others. I also present analysis of real data and simulations applying my method to a simulated epistasis data set. The next section was inspired by the challenges involved in applying a Markov Chain Monte Carlo method to genetic data. It is an investigation into the performance and benefits of the Matlab parallel computing toolbox, specifically its implementation of the Cuda programing language to Matlab's higher level language. Cuda is a language which allows computational calculations to be carried out on the computer's graphics processing unit (GPU) rather than its central processing unit (CPU). The appeal of this tool box is its ease of use as few code adaptions are needed. The final project of this thesis was to develop an HMM for reconstructing the founders of sparsely sequenced inbred populations. The motivation here, that whilst sequencing costs are rapidly decreasing, it is still prohibitively expensive to fully sequence a large number of individuals. It was proposed that, for populations descended from a known number of founders, it would be possible to sequence these individuals with a very low coverage, use a hidden Markov model (HMM) to represent the chromosomes as mosaics of the founders, then use these states to impute the missing data. For this I developed a Viterbi algorithm with a transition probability matrix based on recombination rate which changes for each observed state.
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Finucane, Hilary Kiyo. "Functional and cross-trait genetic architecture of common diseases and complex traits." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112906.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 2017
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 201-245).
In this thesis, I introduce new methods for learning about diseases and traits from genetic data. First, I introduce a method for partitioning heritability by functional annotation from genome-wide association summary statistics, and I apply it to 17 diseases and traits and many different functional annotations. Next, I show how to apply this method to use gene expression data to identify diseaserelevant tissues and cell types. I next introduce a method for estimating genetic correlation from genome-wide association summary statistics and apply it to estimate genetic correlations between all pairs of 24 diseases and traits. Finally, I consider a model of disease subtypes and I show how to determine a lower bound on the sample size required to distinguish between two disease subtypes as a function of several parameters.
by Hilary Kiyo Finucane.
Ph. D.
Ph.D. Massachusetts Institute of Technology, Department of Mathematics
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Sharma, Pankaj. "Genetic dissection of complex traits : essential hypertension." Thesis, University of Cambridge, 1998. https://www.repository.cam.ac.uk/handle/1810/275234.

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Chin, Brian L. (Brian Leland). "Molecular mechanisms controlling complex traits in yeast." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/72804.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biology, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references.
A fundamental goal in biology is to understand how the information stored in DNA results in a cellular function. However, it is insufficient to study one variant of a particular DNA sequence because most people do not share identical genome sequences, and the differences in DNA sequence have functional consequences. In this thesis, I examine how natural variation in the Saccharomyces cerevisiae genome can affect cellular processes. This is done using deletion libraries to examine how mutations in the same gene but in two different genetic backgrounds of S. cerevisiae, S288c and [summation]1278b, can lead different phenotypes for two traits: gene essentiality and agar adhesion. We found that the genomes of the S288c and [summation]1278b strains are only as divergent as two humans in the population. However, analyses of deletion libraries in each strain revealed 57 genes have functions that are essential in one strain but not the other. Strain specific phenotypes are more pronounced for the trait of agar adhesion where 553 deletions have phenotypes that are specific to one strain or the other. Part of the difference is because the [summation]1278b strain requires the filamentation mitogen activated kinase pathway (fMAPK) for agar adhesion but the S288c strain does not. I found that S288c is able to bypass the fMAPK pathway because it contains an allele of the transcription factor RPI1 that promotes transcription of the gene FLO11. Characterization of the sequence differences between the S288c and 11278b alleles of RPIJ revealed that they differ in the number of intragenic tandem repeats. Examination of the genomes of both strains uncovered the possibility that expansions and contractions of intragenic repeats may be a general mechanism to quickly introduce genomic and phenotypic variation.
by Brian L. Chin.
Ph.D.
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Groves-Kirkby, Nick. "Genetic analysis of variation in complex traits." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:4541c4e4-4538-4348-bb4b-0df6673344d2.

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Variation is a universal property of life, and much of contemporary genetics research is directed towards understanding the causes of variation in traits. Here I present the results of my investigations into the genetic and other causes of trait variation in humans and mice. I address these questions in the context of two distinct research projects, which use pre-existing data to investigate the causes of trait variation, through a range of analytic techniques. I first extract trait data from historic breeding records from the incipient Collaborative Cross (a genetic reference population of recombinant inbred mice) and use them to map genetic factors affecting litter size and other reproductive traits. Mapping reveals significant quantitative trait loci associated with litter size and time between litters, as well as a number of suggestive loci. I characterise the genetic effects at these loci and investigate candidate genes. The most robust finding, a litter size locus on chromosome 5, explains around 3% of observed variation and 24% of the variation attributable to genetics. Using data obtained from the Netherlands Twin Registry - a longitudinal database of Dutch twins - I investigate the prevalence of parent of origin effects on gene expression traits in peripheral blood in humans. I first phase individuals' genotypes by parental origin and use these genotypes to calculate the heritability of over 44,000 gene expression traits partitioned into that attributable to matching and nonmatching parent of origin. I replicate prior genomewide heritability estimates for many traits, but I find little evidence of widespread parent-of-origin effects on human gene expression in blood. On further examination, the small sample size severely limits the power to detect such effects. Nonetheless, I identify approximately 200 genes enriched for immune system processes that show evidence of parent-of-origin-specific effects on heritability.
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Weissglas, Daphna. "Gene identification for complex cardiovascular lipid traits." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1875374471&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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Books on the topic "Complex traits"

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1947-, Fischer Ernst Peter, Hood Leroy E, and Möller Gerald, eds. Complex traits. München: Piper, 1997.

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Naumova, Anna K., and Celia M. T. Greenwood, eds. Epigenetics and Complex Traits. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5.

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1960-, Paterson Andrew H., ed. Molecular dissection of complex traits. Boca Raton, Fla: CRC Press, 1998.

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C, Rao D., and Province Michael Arthur, eds. Genetic dissection of complex traits. San Diego: Academic Press, 2001.

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C, Rao D., and Gu C. Charles, eds. Genetic dissection of complex traits. 2nd ed. London: Academic Press, 2008.

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Zeggini, Eleftheria, and Andrew Morris, eds. Assessing Rare Variation in Complex Traits. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4939-2824-8.

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1955-, Saxton Arnold Myron, and SAS Institute, eds. Genetic analysis of complex traits using SAS. Cary, N.C: SAS Institute, 2004.

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service), ScienceDirect (Online, ed. Computational methods for genetics of complex traits. London: Academic Press, 2010.

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Fan, Ruixue. On Identifying Rare Variants for Complex Human Traits. [New York, N.Y.?]: [publisher not identified], 2015.

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Indian National Confederation and Academy of Anthropologists, ed. Mapping complex traits in the adriatic islands: Anthropology laid the foundation. Jhargram: Indian National Confederation and Academy of Anthropologists, 2014.

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Book chapters on the topic "Complex traits"

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Singh, Abanish. "Complex Traits." In Encyclopedia of Behavioral Medicine, 478–79. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_680.

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Singh, Abanish. "Complex Traits." In Encyclopedia of Behavioral Medicine, 529. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_680.

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Bailey, Ernest, and Samantha A. Brooks. "Genetics of complex traits." In Horse genetics, 188–96. Wallingford: CABI, 2020. http://dx.doi.org/10.1079/9781786392589.0188.

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Maupetit-Méhouas, Stéphanie, David Nury, and Philippe Arnaud. "Epigenetic Reprogramming in the Mammalian Germline." In Epigenetics and Complex Traits, 3–34. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_1.

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Furrow, Robert E., Freddy B. Christiansen, and Marcus W. Feldman. "Epigenetic Variation, Phenotypic Heritability, and Evolution." In Epigenetics and Complex Traits, 233–46. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_10.

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Sinsheimer, Janet S., and Michelle M. Creek. "Statistical Approaches for Detecting Transgenerational Genetic Effects in Humans." In Epigenetics and Complex Traits, 247–64. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_11.

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Labbe, Aurélie, Lam Opal Huang, and Claire Infante-Rivard. "Transmission Ratio Distortion: A Neglected Phenomenon with Many Consequences in Genetic Analysis and Population Genetics." In Epigenetics and Complex Traits, 265–85. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_12.

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Bell, Christopher G. "Epigenome-Wide Association Studies: Potential Insights into Human Disease." In Epigenetics and Complex Traits, 287–317. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_13.

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Bell, Jordana T. "Analytical Considerations for Epigenome-Wide Association Scans of Complex Traits." In Epigenetics and Complex Traits, 319–38. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_14.

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Sandovici, Ionel. "Establishment of Tissue-Specific Epigenetic States During Development." In Epigenetics and Complex Traits, 35–62. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8078-5_2.

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Conference papers on the topic "Complex traits"

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Conti, Vincenzo, Salvatore Vitabile, and Filippo Sorbello. "Fingerprint Traits and RSA Algorithm Fusion Technique." In 2012 Sixth International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS). IEEE, 2012. http://dx.doi.org/10.1109/cisis.2012.116.

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Huh, Ik-Soo, Sohee Oh, Eunjin Lee, and Taesung Park. "Compairing quantitative trait analysis to qualitative trait analysis for complex traits disease: A genome wide association study for hyperlipidemia." In 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2010. http://dx.doi.org/10.1109/bibmw.2010.5703825.

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Gnennyi, E. Yu. "VARIABILITY OF RICE PLANT TRAITS WHEN GROWING WITHOUT IRRIGATION." In INNOVATIVE DEVELOPMENT OF THE AGRO-INDUSTRIAL COMPLEX: NEW APPROACHES AND RELEVANT RESEARCH, 68–75. Federal Scientific Rice Centre, 2024. http://dx.doi.org/10.33775/conf-2024-68-75.

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Gamazon, Eric R., Hae Kyung Im, Bonnie LaCroix, Dana Ziliak, and R. Stephanie Huang. "Abstract 1643: MicroRNA processing genes and implications for complex traits." In Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL. American Association for Cancer Research, 2012. http://dx.doi.org/10.1158/1538-7445.am2012-1643.

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Sarkar, Aisharjya, Aaditya Singh, Richard Bailey, Alin Dobra, and Tamer Kahveci. "Optimal separation of high dimensional transcriptome for complex multigenic traits." In BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3535508.3545506.

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"Gene duplications drive the evolution of complex traits and regulation." In ECAL 2017, the Fourteenth European Conference on Artificial Life. MIT Press, 2017. http://dx.doi.org/10.1162/isal_a_045.

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Lalejini, Alexander, Michael J. Wiser, and Charles Ofria. "Gene duplications drive the evolution of complex traits and regulation." In Proceedings of the 14th European Conference on Artificial Life ECAL 2017. Cambridge, MA: MIT Press, 2017. http://dx.doi.org/10.7551/ecal_a_045.

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Zhu, Qi. "Using Linear Discriminant Analysis to Fuse Bimodal Biometrics Traits in Complex Space." In 2012 4th International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, 2012. http://dx.doi.org/10.1109/cicn.2012.203.

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Sun, Jiangwen, Jinbo Bi, and Henry R. Kranzler. "Quadratic optimization to identify highly heritable quantitative traits from complex phenotypic features." In KDD' 13: The 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2487575.2487621.

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Evans, Scott, Douglas Erwin, Ian Hughes, and Mary Droser. "CHARACTERS OF THE EDIACARAN: IDENTIFYING COMPLEX TRAITS IN EARTH’S EARLIEST FOSSIL ANIMALS." In GSA Connects 2023 Meeting in Pittsburgh, Pennsylvania. Geological Society of America, 2023. http://dx.doi.org/10.1130/abs/2023am-389986.

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Reports on the topic "Complex traits"

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Cahaner, Avigdor, Susan J. Lamont, E. Dan Heller, and Jossi Hillel. Molecular Genetic Dissection of Complex Immunocompetence Traits in Broilers. United States Department of Agriculture, August 2003. http://dx.doi.org/10.32747/2003.7586461.bard.

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Objectives: (1) Evaluate Immunocompetence-OTL-containing Chromosomal Regions (ICRs), marked by microsatellites or candidate genes, for magnitude of direct effect and for contribution to relationships among multiple immunocompetence, disease-resistance, and growth traits, in order to estimate epistatic and pleiotropic effects and to predict the potential breeding applications of such markers. (2) Evaluate the interaction of the ICRs with genetic backgrounds from multiple sources and of multiple levels of genetic variation, in order to predict the general applicability of molecular genetic markers across widely varied populations. Background: Diseases cause substantial economic losses to animal producers. Emerging pathogens, vaccine failures and intense management systems increase the impact of diseases on animal production. Moreover, zoonotic pathogens are a threat to human food safety when microbiological contamination of animal products occurs. Consumers are increasingly concerned about drug residues and antibiotic- resistant pathogens derived from animal products. The project used contemporary scientific technologies to investigate the genetics of chicken resistance to infectious disease. Genetic enhancement of the innate resistance of chicken populations provides a sustainable and ecologically sound approach to reduce microbial loads in agricultural populations. In turn, animals will be produced more efficiently with less need for drug treatment and will pose less of a potential food-safety hazard. Major achievements, conclusions and implications:. The PI and co-PIs had developed a refined research plan, aiming at the original but more focused objectives, that could be well-accomplished with the reduced awarded support. The successful conduct of that research over the past four years has yielded substantial new information about the genes and genetic markers that are associated with response to two important poultry pathogens, Salmonella enteritidis (SE) and Escherichia coli (EC), about variation of immunocompetence genes in poultry, about relationships of traits of immune response and production, and about interaction of genes with environment and with other genes and genetic background. The current BARD work has generated a base of knowledge and expertise regarding the genetic variation underlying the traits of immunocompetence and disease resistance. In addition, unique genetic resource populations of chickens have been established in the course of the current project, and they are essential for continued projects. The US laboratory has made considerable progress in studies of the genetics of resistance to SE. Microsatellite-marked chromosomal regions and several specific genes were linked to SE vaccine response or bacterial burden and the important phenomenon of gene interaction was identified in this system. In total, these studies demonstrate the role of genetics in SE response, the utility of the existing resource population, and the expertise of the research group in conducting such experiments. The Israeli laboratories had showed that the lines developed by selection for high or low level of antibody (Ab) response to EC differ similarly in Ab response to several other viral and bacterial pathogens, indicating the existence of a genetic control of general capacity of Ab response in young broilers. It was also found that the 10w-Ab line has developed, possibly via compensatory "natural" selection, higher cellular immune response. At the DNA levels, markers supposedly linked to immune response were identified, as well as SNP in the MHC, a candidate gene responsible for genetic differences in immunocompetence of chickens.
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Nagahi, Morteza, Raed Jaradat, Simon Goerger, Michael Hamilton, Randy Buchanan, Sawsan Abutabenjeh, and Junfeng Ma. The impact of practitioners’ personality traits on their level of systems-thinking skills preferences. Engineer Research and Development Center (U.S.), October 2022. http://dx.doi.org/10.21079/11681/45791.

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In this study, we used a structural equation modeling method to investigate the relationship between systems engineers and engineering managers’ Systems-Thinking (ST) skills preferences and their Personality Traits (PTs) in the domain of complex system problems. As organizations operate in more and more turbulent and complex environments, it has become increasingly important to assess the ST skills preferences and PTs of engineers. The current literature lacks studies related to the impact of systems engineers and engineering managers’ PTs on their ST skills preferences, and this study aims to address this gap. A total of 99 engineering managers and 104 systems engineers provided the data to test four hypotheses posed in this study. The results show that the PTs of systems engineers and engineering managers have a positive impact on their level of ST skills preferences and that the education level, the current occupation type, and the managerial experience of the systems engineers and engineering managers moderate the main relationship in the study.
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Hulata, Gideon, and Graham A. E. Gall. Breed Improvement of Tilapia: Selective Breeding for Cold Tolerance and for Growth Rate in Fresh and Saline Water. United States Department of Agriculture, November 2003. http://dx.doi.org/10.32747/2003.7586478.bard.

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The main objective of this project was to initiate a breeding program to produce cold-tolerant and salinity-tolerant synthetic breeds of tilapia, from a base population consisting of a four-species hybrid population created under an earlier BARD project. A secondary objective was to estimate genetic parameters for the traits growth rate under fresh- and salt-water and for cold tolerance. A third objective was to place quantitative trait loci that affect these traits of interest (e.g., growth rate in fresh-water, salt-water and cold tolerance) on the growing linkage map of primarily microsatellite loci. We have encountered fertility problems that were apparently the result of the complex genetic structure of this base population. The failure in producing the first generation of the breeding program has forced us to stop the intended breeding program. Thus, upon approval of BARD office, this objective was dropped and during the last year we have focused on the secondary objective of the original project during the third year of the project, but failed to perform the intended analysis to estimate genetic parameters for the traits of interest. We have succeeded, however, to strengthen the earlier identification of a QTL for cold tolerance by analyzing further segregating families. The results support the existence of a QTL for cold tolerance on linkage group 15, corresponding to UNH linkage group 23. The results also indicate a QTL for the same trait on linkage group 12, corresponding to UNH linkage group 4.
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Seroussi, Eyal, and George Liu. Genome-Wide Association Study of Copy Number Variation and QTL for Economic Traits in Holstein Cattle. United States Department of Agriculture, September 2010. http://dx.doi.org/10.32747/2010.7593397.bard.

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Copy number variation (CNV) has been recently identified in human and other mammalian genomes and increasing awareness that CNV might be a major source for heritable variation in complex traits has emerged. Despite this, little has been published on CNVs in Holsteins. In order to fill this knowledge-gap, we proposed a genome-wide association study between quantitative trait loci (QTL) for economic traits and CNV in the Holstein cattle. The approved feasibility study was aimed at the genome-wide characterization of CNVs in Holstein cattle and at the demonstrating of their possible association with economic traits by performing the activities of preparation of DNA samples, Comparative Genomic Hybridization (CGH), initial association study between CNVs and production traits and characterization of CNVSNP associations. For both countries, 40 genomic DNA samples of bulls representing the extreme sub-populations for economically important traits were CGH analyzed using the same reference genome on a NimbleGen tiling array. We designed this array based on the latest build of the bovine genome (UMD3) with average probe spacing of 1150 bases (total number of probes was 2,166,672). Two CNV gene clusters, PLA2G2D on BTA2 and KIAA1683 on BTA7 revealed significant association with milk percentage and cow fertility, respectively, and were chosen for further characterization and verification in a larger sample using other methodologies including sequencing, tag SNPs and real time PCR (qPCR). Comparison between these four methods indicated that there is under estimation of the number of CNV loci in Holstein cattle and their complexity. The variation in sequence between different copies seemed to affect their functionality and thus the hybridization based methods were less informative than the methods that are based on sequencing. We thus conclude that large scale sequencing effort complemented by array CGH should be considered to better detect and characterize CNVs in order to effectively employ them in marker-assisted selection.
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Jung, Carina, Karl Indest, Matthew Carr, Richard Lance, Lyndsay Carrigee, and Kayla Clark. Properties and detectability of rogue synthetic biology (SynBio) products in complex matrices. Engineer Research and Development Center (U.S.), September 2022. http://dx.doi.org/10.21079/11681/45345.

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Synthetic biology (SynBio) aims to rationally engineer or modify traits of an organism or integrate the behaviors of multiple organisms into a singular functional organism through advanced genetic engineering techniques. One objective of this research was to determine the environmental persistence of engineered DNA in the environment. To accomplish this goal, the environmental persistence of legacy engineered DNA building blocks were targeted that laid the foundation for SynBio product development and application giving rise to “post-use products.” These building blocks include genetic constructs such as cloning and expression vectors, promoter/terminator elements, selectable markers, reporter genes, and multi-cloning sites. Shotgun sequencing of total DNA from water samples of pristine sites was performed and resultant sequence data mined for frequency of legacy recombinant DNA signatures. Another objective was to understand the fate of a standardized contemporary synthetic genetic construct (SC) in the context of various chassis systems/genetic configurations representing different degrees of “genetic bioavailability” to the environmental landscape. These studies were carried out using microcosms representing different environmental matrices (soils, waters, wastewater treatment plant (WWTP) liquor) and employed a novel genetic reporter system based on volatile organic compounds (VOC) detection to assess proliferation and persistence of the SC in the matrix over time.
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Weller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu, and George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600017.bard.

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The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed.
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Lamont, Susan J., E. Dan Heller, and Avigdor Cahaner. Prediction of Immunocompetence and Resistance to Disease by Using Molecular Markers of the Major Histocompatibility Complex. United States Department of Agriculture, September 1994. http://dx.doi.org/10.32747/1994.7568780.bard.

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This project utilized two live-animal populations in an integrated research program to identify molecular markers for immune response and disease resistance. The populations each had their foundation from meat-type commercial breeder chicken lines of their respective countries. Investigations effectively used unique availability of resources in each country to study commercial-type environments in Israel and line-crosses with diverse inbred lines in the US. Two bacterial systems were investigated to cover both respiratory and gastrointestinal, and primary and secondary, infections. Individual experimental groups of animals were evaluated for combinations of vaccine antibody levels, response to pathogen challenge, growth parameters, genetic background and molecular markers. The positive association of antibody level with resistance to disease was confirmed. Effectiveness of genetic selection for vaccine antibody response level was demonstrated. Molecular markers, both inside and outside the MHC region, were associated with antibody response and resistance to disease. Markers were shown to have a generalized effect, by association with multiple traits of immune response and disease resistance. The impact of genetic background on marker effect was shown to be important. The overall results demonstrate the effectiveness of selection on vaccine antibody response and the potential of molecular marker-assisted selection to improve efficiency of production of meat-type chickens by reducing genetic susceptibility to disease.
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Rajarajan, Kunasekaran, Alka Bharati, Hirdayesh Anuragi, Arun Kumar Handa, Kishor Gaikwad, Nagendra Kumar Singh, Kamal Prasad Mohapatra, et al. Status of perennial tree germplasm resources in India and their utilization in the context of global genome sequencing efforts. World Agroforestry, 2020. http://dx.doi.org/10.5716/wp20050.pdf.

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Tree species are characterized by their perennial growth habit, woody morphology, long juvenile period phase, mostly outcrossing behaviour, highly heterozygosity genetic makeup, and relatively high genetic diversity. The economically important trees have been an integral part of the human life system due to their provision of timber, fruit, fodder, and medicinal and/or health benefits. Despite its widespread application in agriculture, industrial and medicinal values, the molecular aspects of key economic traits of many tree species remain largely unexplored. Over the past two decades, research on forest tree genomics has generally lagged behind that of other agronomic crops. Genomic research on trees is motivated by the need to support genetic improvement programmes mostly for food trees and timber, and develop diagnostic tools to assist in recommendation for optimum conservation, restoration and management of natural populations. Research on long-lived woody perennials is extending our molecular knowledge and understanding of complex life histories and adaptations to the environment, enriching a field that has traditionally drawn its biological inference from a few short-lived herbaceous species. These concerns have fostered research aimed at deciphering the genomic basis of complex traits that are related to the adaptive value of trees. This review summarizes the highlights of tree genomics and offers some priorities for accelerating progress in the next decade.
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Veilleux, Richard, and David Levy. Potato Germplasm Development for Warm Climates. United States Department of Agriculture, October 1992. http://dx.doi.org/10.32747/1992.7561057.bard.

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Complex potato hybrids derived from crosses between cv. Atlantic and 11 clones of three genomic compositions, all with an unadapted component from previously identified heat tolerant accessions, were evaluated in the field in Israel and Virginia and in controlled environments in Israel. Heat tolerance was exhibited in the field by the ability of many of these hybrids to tuberize under severe heat stress when cv. Atlantic did not tuberize at all. The complex hybrids also exhibited fewer internal defects (heat necrosis, hollow heart) than Atlantic. Studies to determine if heat stress applied during anther culture or to pollen samples prior to pollination could affect gametic selection towards more heat tolerant progenies were also undertaken. There was some evidence of greater heat tolerance (longer survival under heat stress) in the anther-derived population that had been regenerated under heat stress. The seedlings resulting from crosses with heat-treated pollen also exhibited greater haulm growth under heat stress compared with controls. However, the poor adaption of the germplasm prevented a firm conclusion about gametic selection. The introduction of exotic germplasm into cultivated potato has considerable potential to adapt potato to nontraditional growing seasons and climates. However, such hybrids will require continued selection and evaluation to retain the traits required for commercial production.
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Ohad, Nir, and Robert Fischer. Regulation of plant development by polycomb group proteins. United States Department of Agriculture, January 2008. http://dx.doi.org/10.32747/2008.7695858.bard.

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Our genetic and molecular studies have indicated that FIE a WD-repeat Polycomb group (PcG) protein takes part in multi-component protein complexes. We have shown that FIE PcG protein represses inappropriate programs of development during the reproductive and vegetative phases of the Arabidopsis life cycle. Moreover, we have shown that FIE represses the expression of key regulatory genes that promote flowering (AG and LFY), embryogenesis (LEC1), and shoot formation (KNAT1). These results suggest that the FIE PcG protein participates in the formation of distinct PcG complexes that repress inappropriate gene expression at different stages of plant development. PcG complexes modulate chromatin compactness by modifying histones and thereby regulate gene expression and imprinting. The main goals of our original project were to elucidate the biological functions of PcG proteins, and to understand the molecular mechanisms used by FIE PcG complexes to repress the expression of its gene targets. Our results show that the PcG complex acts within the central cell of the female gametophyte to maintain silencing of MEA paternal allele. Further more we uncovered a novel example of self-imprinting mechanism by the PgG complex. Based on results obtained in the cures of our research program we extended our proposed goals and elucidated the role of DME in regulating plant gene imprinting. We discovered that in addition to MEA,DME also imprints two other genes, FWA and FIS2. Activation of FWA and FIS2 coincides with a reduction in 5-methylcytosine in their respective promoters. Since endosperm is a terminally differentiated tissue, the methylation status in the FWA and FIS2 promoters does not need to be reestablished in the following generation. We proposed a “One-Way Control” model to highlight differences between plant and animal genomic imprinting. Thus we conclude that DEMETER is a master regulator of plant gene imprinting. Future studies of DME function will elucidate its role in processes and disease where DNA methylation has a key regulatory role both in plants and animals. Such information will provide valuable insight into developing novel strategies to control and improve agricultural traits and overcome particular human diseases.
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