Academic literature on the topic 'Genomic trait'
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Journal articles on the topic "Genomic trait"
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Bohlouli, Mehdi, Sadegh Alijani, Ardashir Nejati Javaremi, Sven König, and Tong Yin. "Genomic prediction by considering genotype × environment interaction using different genomic architectures." Annals of Animal Science 17, no. 3 (July 26, 2017): 683–701. http://dx.doi.org/10.1515/aoas-2016-0086.
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Abstract In this study, accuracies of genomic prediction across various scenarios were compared using single- trait and multiple-trait animal models to detect genotype × environment (G × E) interaction based on REML method. The simulated high and low linkage disequilibrium (HLD and LLD) genome consisted of 15,000 and 50,000 SNP chip applications with 300 and 600 QTLs controlling the trait of interest. The simulation was done to create the genetic correlations between the traits in 4 environments and heritabilities of the traits were 0.20, 0.25, 0.30 and 0.35 in environments 1, 2, 3 and 4, respectively. Two strategies were used to predict the accuracy of genomic selection for cows without phenotypes. In the first strategy, phenotypes for cows in three environments were kept as a training set and breeding values for all animals were estimated using three-trait model. In the second one, only 25, 50 or 75% of records in the fourth environment and all the records in the other three environments were used to predict GBV for non-phenotyped cows in the environment 4. For the first strategy, the highest accuracy of 0.695 was realized in scenario HLD with 600 QTL and 50K SNP chip for the fourth environment and the lowest accuracy of 0.495 was obtained in scenario LLD with 600QTL and 15K SNP chips for the first environment. Generally, the accuracy of prediction increased significantly (P<0.05) with increasing the number of markers, heritability and the genetic correlation between the traits, but no significant difference was observed between scenarios with 300 and 600 QTL. In comparison with models without G × E interaction, accuracies of the GBV for all environments increased when using multi-trait models. The results showed that the level of LD, number of animals in training set and genetic correlation across environments play important roles if G × E interaction exists. In conclusion, G × E interaction contributes to understanding variations of quantitative trait and increasing accuracy of genomic prediction. Therefore, the interaction should be taken into account in conducting selection in various environments or across different genotypes.
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Lozada, Dennis, and Arron Carter. "Insights into the Genetic Architecture of Phenotypic Stability Traits in Winter Wheat." Agronomy 10, no. 3 (March 7, 2020): 368. http://dx.doi.org/10.3390/agronomy10030368.
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Examining the architecture of traits through genomics is necessary to gain a better understanding of the genetic loci affecting important traits to facilitate improvement. Genomewide association study (GWAS) and genomic selection (GS) were implemented for grain yield, heading date, and plant height to gain insights into the genetic complexity of phenotypic stability of traits in a diverse population of US Pacific Northwest winter wheat. Analysis of variance using the Additive Main Effect and Multiplicative Interaction (AMMI) approach revealed significant genotype and genotype by environment interactions. GWAS identified 12 SNP markers distributed across 10 chromosomes affecting variation for both trait and phenotypic stability, indicating potential pleiotropic effects and signifying that similar genetic loci could be associated with different aspects of stability. The lack of stable and major effect loci affecting phenotypic variation supports the complexity of stability of traits. Accuracy of GS was low to moderate, between 0.14 and 0.66, indicating that phenotypic stability is under genetic control. The moderate to high correlation between trait and trait stability suggests the potential of simultaneous selection for trait and trait stability. Our results demonstrate the complex genetic architecture of trait stability and show the potential for improving stability in winter wheat using genomic-assisted approaches.
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Calus, M. P. L., D. P. Berry, G. Banos, Y. de Haas, and R. F. Veerkamp. "Genomic selection: the option for new robustness traits?" Advances in Animal Biosciences 4, no. 3 (July 2013): 618–25. http://dx.doi.org/10.1017/s2040470013000186.
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Genomic selection is rapidly becoming the state-of-the-art genetic selection methodology in dairy cattle breeding schemes around the world. The objective of this paper was to explore possibilities to apply genomic selection for traits related to dairy cow robustness. Deterministic simulations indicate that replacing progeny testing with genomic selection may favour genetic response for production traits at the expense of robustness traits, owing to a disproportional change in accuracies obtained across trait groups. Nevertheless, several options are available to improve the accuracy of genomic selection for robustness traits. Moreover, genomic selection opens up the opportunity to begin selection for new traits using specialised reference populations of limited size where phenotyping of large populations of animals is currently prohibitive. Reference populations for such traits may be nucleus-type herds, research herds or pooled data from (international) research experiments or research herds. The RobustMilk project has set an example for the latter approach, by collating international data for progesterone-based traits, feed intake and energy balance-related traits. Reference population design, both in terms of relatedness of the animals and variability in phenotypic performance, is important to optimise the accuracy of genomic selection. Use of indicator traits, combined with multi-trait genomic prediction models, can further contribute to improved accuracy of genomic prediction for robustness traits. Experience to date indicates that for newly recorded robustness traits that are negatively correlated with the main breeding goal, cow reference populations of ⩾10 000 are required when genotyping is based on medium- or high-density single-nucleotide polymorphism arrays. Further genotyping advances (e.g. sequencing) combined with post-genomics technologies will enhance the opportunities for (genomic) selection to improve cow robustness.
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Sunagar, Ramesh, and Manoj Kumar Pandey. "Genomic Approaches for Enhancing Yield and Quality Traits in Mustard (Brassica spp.): A Review of Breeding Strategies." Journal of Advances in Biology & Biotechnology 27, no. 6 (May 8, 2024): 174–85. http://dx.doi.org/10.9734/jabb/2024/v27i6877.
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Mustard, a vital oilseed crop, plays a significant role in global agriculture due to its versatile applications in food, feed, and biofuel industries. However, meeting the increasing demands for yield and quality traits poses a substantial challenge to mustard breeders. In response, genomic approaches have emerged as powerful tools to expedite mustard breeding programs by unraveling the genetic basis of key agronomic traits. This review provides a comprehensive overview of genomic strategies aimed at enhancing yield and quality traits in mustard. Beginning with an exploration of traditional breeding methods and their limitations, we delve into the advancements in genomics, including next-generation sequencing technologies, marker-assisted selection (MAS), and genome editing techniques. We discuss how these tools are leveraged to identify yield-related genes, quantitative trait loci (QTLs), and markers for efficient trait selection. Furthermore, we examine genomic approaches for improving oil content, nutritional profiles, and phytochemical composition, crucial for enhancing mustard quality. Case studies demonstrating the successful integration of genomics into breeding programs are highlighted, along with discussions on challenges such as regulatory concerns and technical hurdles. Finally, we outline future directions and the potential of genomic approaches to revolutionize mustard breeding, paving the way for sustainable crop improvement. This study offers valuable insights into the application of genomics in mustard breeding and underscores its importance in addressing the evolving needs of agriculture in the 21st century.
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Srivastava, Swati, Bryan Irvine Lopez, Sara de las Heras-Saldana, Jong-Eun Park, Dong-Hyun Shin, Han-Ha Chai, Woncheol Park, Seung-Hwan Lee, and Dajeong Lim. "Estimation of Genetic Parameters by Single-Trait and Multi-Trait Models for Carcass Traits in Hanwoo Cattle." Animals 9, no. 12 (December 2, 2019): 1061. http://dx.doi.org/10.3390/ani9121061.
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Hanwoo breed is preferred in South Korea because of the high standards in marbling and the palatability of its meat. Numerous studies have been conducted and are ongoing to increase the meat production and quality in this beef population. The aim of this study was to estimate and compare genetic parameters for carcass traits using BLUPF90 software. Four models were constructed, single trait pedigree model (STPM), single-trait genomic model (STGM), multi-trait pedigree model (MTPM), and multi-trait genomic model (MTGM), using the pedigree, phenotype, and genomic information of 7991 Hanwoo cattle. Four carcass traits were evaluated: Back fat thickness (BFT), carcass weight (CWT), eye muscle area (EMA), and marbling score (MS). Heritability estimates of 0.40 and 0.41 for BFT, 0.33 and 0.34 for CWT, 0.36 and 0.37 for EMA, and 0.35 and 0.38 for MS were obtained for the single-trait pedigree model and the multi-trait pedigree model, respectively, in Hanwoo. Further, the genomic model showed more improved results compared to the pedigree model, with heritability of 0.39 (CWT), 0.39 (EMA), and 0.46 (MS), except for 0.39 (BFT), which may be due to random events. Utilization of genomic information in the form of single nucleotide polymorphisms (SNPs) has allowed more capturing of the variance from the traits improving the variance components.
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Huang, Mao, Antonio Cabrera, Amber Hoffstetter, Carl Griffey, David Van Sanford, José Costa, Anne McKendry, Shiaoman Chao, and Clay Sneller. "Genomic selection for wheat traits and trait stability." Theoretical and Applied Genetics 129, no. 9 (June 4, 2016): 1697–710. http://dx.doi.org/10.1007/s00122-016-2733-z.
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Eduardo, Iban, Pere Arús, Antonio José Monforte, Javier Obando, Juan Pablo Fernández-Trujillo, Juan Antonio Martínez, Antonio Luís Alarcón, Jose María Álvarez, and Esther van der Knaap. "Estimating the Genetic Architecture of Fruit Quality Traits in Melon Using a Genomic Library of Near Isogenic Lines." Journal of the American Society for Horticultural Science 132, no. 1 (January 2007): 80–89. http://dx.doi.org/10.21273/jashs.132.1.80.
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A melon (Cucumis melo L.) genomic library of near-isogenic lines derived from the cross between the Spanish cultivar Piel de Sapo and the exotic accession PI 161375 has been evaluated for fruit quality traits in four different locations. Traits evaluated were fruit weight, soluble solids content, maximum fruit diameter, fruit length, fruit shape index, ovary shape index, external color, and flesh color. Among these traits, soluble solids content showed the highest genotype × environment interaction, whereas genotype × environment interactions for fruit shape and fruit weight were low. Heritability was high for all traits except soluble solids content, with the highest value for fruit shape and ovary shape. Ten to 15 quantitative trait loci were detected for soluble solids content, fruit diameter, fruit length, and fruit shape; and four to five for ovary shape, external color, and flesh color. Depending on the trait, between 13% and 40% of the detected quantitative trait alleles from PI 161375 increased the trait, and between 60% and 87% of them decreased it, resulting in some PI 161375 alleles of interest for breeding. Most of the quantitative trait loci detected in previous experiments could be verified with the near-isogenic line population. Future studies with the melon near-isogenic line genomic library will provide a better understanding of the genetic control of melon fruit quality in a wider context related to agronomy, genetics, genomics and metabolomics studies.
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Fragomeni, Breno, Zulma Vitezica, Justine Liu, Yijian Huang, Kent Gray, Daniela Lourenco, and Ignacy Misztal. "209 Genomic selection for multiple maternal and growth traits in large white pigs using Single-Step GBLUP." Journal of Animal Science 97, Supplement_3 (December 2019): 42. http://dx.doi.org/10.1093/jas/skz258.084.
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Abstract The objective of this study was to implement a multi-trait genomic evaluation for maternal and growth traits in a swine population. Phenotypes for preweaning mortality, litter size, weaning weight, and average daily gain were available for 282K Large White pigs. The pedigree included 314k individuals, of which 35,731 were genotyped for 45K SNPs. Variance components were estimated in a multi-trait animal model without genomic information by AIREMLF90. Genomic breeding values were estimated using the genomic information by single-step GBLUP. The algorithm for proven and young (APY) was used to reduce computing time. Genetic correlation between proportion and the total number of preweaning deaths was 0.95. A strong, positive genetic correlation was also observed between weaning weight and average daily gain (r = 0.94). Conversely, the genetic correlations between mortality and growth traits were negative, with an average of -0.7. To avoid computations by expensive threshold models, preweaning mortality was transformed from a binary trait to two linear dam traits: proportion and a total number of piglets dead before weaning. Because of the high genetic correlations within groups of traits, inclusion of only one growth and one mortality trait in the model decreases computing time and allows for the inclusion of other traits. Reduction in computing time for the evaluation using APY was up to 20x, and no differences in EPD ranking were observed. The algorithm for proven and young improves the efficiency of genomic evaluation in swine without harming the quality of predictions. For this population, a binary trait of mortality can be replaced by a linear trait of the dam, resulting in a similar ranking for the selection candidates.
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Shabannejad, Morteza, Mohammad-Reza Bihamta, Eslam Majidi-Hervan, Hadi Alipour, and Asa Ebrahimi. "A classic approach for determining genomic prediction accuracy under terminal drought stress and well-watered conditions in wheat landraces and cultivars." PLOS ONE 16, no. 3 (March 5, 2021): e0247824. http://dx.doi.org/10.1371/journal.pone.0247824.
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The present study aimed to improve the accuracy of genomic prediction of 16 agronomic traits in a diverse bread wheat (Triticum aestivum L.) germplasm under terminal drought stress and well-watered conditions in semi-arid environments. An association panel including 87 bread wheat cultivars and 199 landraces from Iran bread wheat germplasm was planted under two irrigation systems in semi-arid climate zones. The whole association panel was genotyped with 9047 single nucleotide polymorphism markers using the genotyping-by-sequencing method. A number of 23 marker-trait associations were selected for traits under each condition, whereas 17 marker-trait associations were common between terminal drought stress and well-watered conditions. The identified marker-trait associations were mostly single nucleotide polymorphisms with minor allele effects. This study examined the effect of population structure, genomic selection method (ridge regression-best linear unbiased prediction, genomic best-linear unbiased predictions, and Bayesian ridge regression), training set size, and type of marker set on genomic prediction accuracy. The prediction accuracies were low (-0.32) to moderate (0.52). A marker set including 93 significant markers identified through genome-wide association studies with P values ≤ 0.001 increased the genomic prediction accuracy for all traits under both conditions. This study concluded that obtaining the highest genomic prediction accuracy depends on the extent of linkage disequilibrium, the genetic architecture of trait, genetic diversity of the population, and the genomic selection method. The results encouraged the integration of genome-wide association study and genomic selection to enhance genomic prediction accuracy in applied breeding programs.
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Moeinizade, Saba, Aaron Kusmec, Guiping Hu, Lizhi Wang, and Patrick S. Schnable. "Multi-trait Genomic Selection Methods for Crop Improvement." Genetics 215, no. 4 (June 1, 2020): 931–45. http://dx.doi.org/10.1534/genetics.120.303305.
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Plant breeders make selection decisions based on multiple traits, such as yield, plant height, flowering time, and disease resistance. A commonly used approach in multi-trait genomic selection is index selection, which assigns weights to different traits relative to their economic importance. However, classical index selection only optimizes genetic gain in the next generation, requires some experimentation to find weights that lead to desired outcomes, and has difficulty optimizing nonlinear breeding objectives. Multi-objective optimization has also been used to identify the Pareto frontier of selection decisions, which represents different trade-offs across multiple traits. We propose a new approach, which maximizes certain traits while keeping others within desirable ranges. Optimal selection decisions are made using a new version of the look-ahead selection (LAS) algorithm, which was recently proposed for single-trait genomic selection, and achieved superior performance with respect to other state-of-the-art selection methods. To demonstrate the effectiveness of the new method, a case study is developed using a realistic data set where our method is compared with conventional index selection. Results suggest that the multi-trait LAS is more effective at balancing multiple traits compared with index selection.
Dissertations / Theses on the topic "Genomic trait"
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Kindt, Alida Sophie Dorothea. "Genomic signature of trait-associated variants." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9620.
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Genome-wide association studies have been used extensively to study hundreds of phenotypes and have determined thousands of associated SNPs whose underlying biology and causation is as yet largely unknown. Many previous studies attempted to clarify the causal biology by investigating overlaps of trait-associated variants with functional annotations, but lacked statistical rigor and examined incomplete subsets of available functional annotations. Additionally, it has been difficult to disentangle the relative contributions of different annotations that may show strong correlations with one another. In this thesis, we address these shortcomings and strengthen and extend the obtained results. Two methods, permutations and logistic regression, are applied in statistically rigorous analyses of genomic annotations and their observed enrichment or depletion of trait-associated SNPs. The genomic annotations range from genic regions and regulatory features to measures of conservation and aspects of chromatin structure. Logistic regressions in a number of trait-specific subsets identify genomic annotations influencing SNPs associated with both normal variation (e.g., eye or hair colour) and diseases, suggesting some generalities in the biological underpinnings of phenotypes. SNPs associated with phenotypes of the immune system are investigated and the results highlight the distinct aetiology for this subset. Despite the heterogeneity of the studied cancers, SNPs associated to different cancers are particularly enriched for conserved regions, unlike all other trait-subsets. Nonetheless, chromatin states are, perhaps surprisingly, among the most influential genomic annotations in all trait-subsets. Evolutionary conserved regions are rarely within the top genomic annotations despite their widespread use in prioritisation methods for follow-up studies. We identify a common set of enriched or depleted genomic annotations that significantly influence all traits, but also highlight trait-‐specific differences. These annotations may be used for the computational prioritisation of variants implicated in phenotypes of interest. The approaches developed for this thesis are further applied to studies of a specific human complex trait (height) and gene expression in atherosclerosis.
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Hu, Wei. "Genomic determinants of alcohol effects /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2008. http://proquest.umi.com/pqdweb?did=1545571871&sid=1&Fmt=6&clientId=18952&RQT=309&VName=PQD.
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Thesis (Ph.D. in Pharmacology) -- University of Colorado Denver, 2008.Typescript. Includes bibliographical references (leaves 121-149). Free to UCD Anschutz Medical Campus. Online version available via ProQuest Digital Dissertations;
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Huang, Mao. "Accuracy of genomic selection in a soft winter wheat (Triticum aestivum L.) breeding program." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1468841458.
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Ward, Brian Phillip. "Genomic Prediction and Genetic Dissection of Yield-Related Traits in Soft Red Winter Wheat." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/85503.
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In multiple species, genome-wide association (GWA) studies have become an increasingly
prevalent method of identifying the quantitative trait loci (QTLs) that underlie complex traits.
Despite this, relatively few GWA analyses using high-density genomic markers have been
carried out on highly quantitative traits in wheat. We utilized single-nucleotide polymorphism
(SNP) data generated via a genotyping-by-sequencing (GBS) protocol to perform GWA on
multiple yield-related traits using a panel of 329 soft red winter wheat genotypes grown in four
environments. In addition, the SNP data was used to examine linkage disequilibrium and
population structure within the testing panel. The results indicated that an alien translocation
from the species Triticum timopheevii was responsible for the majority of observed population
structure. In addition, a total of 50 significant marker-trait associations were identified. However,
a subsequent study cast some doubt upon the reproducibility and reliability of plant QTLs
identified via GWA analyses. We used two highly-related panels of different genotypes grown in
different sets of environments to attempt to identify highly stable QTLs. No QTLs were shared
across panels for any trait, suggesting that QTL-by-environment and QTL-by-genetic
background interaction effects are significant, even when testing across many environments. In
light of the challenges involved in QTL mapping, prediction of phenotypes using whole-genome
marker data is an attractive alternative. However, many evaluations of genomic prediction in
crop species have utilized univariate models adapted from animal breeding. These models cannot
directly account for genotype-by-environment interaction, and hence are often not suitable for
use with lower-heritability traits assessed in multiple environments. We sought to test genomic
prediction models capable of more ad-hoc analyses, utilizing highly unbalanced experimental
designs consisting of individuals with varying degrees of relatedness. The results suggest that
these designs can successfully be used to generate reasonably accurate phenotypic predictions. In addition, multivariate models can dramatically increase predictive accuracy for some traits,
though this depends upon the quantity and characteristics of genotype-by-environment
interaction.Ph. D.
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Masekoameng, Tshepiso. "Sickle cell trait and targeted genomic variants in chronic kidney disease an African cohort." Master's thesis, Faculty of Health Sciences, 2019. http://hdl.handle.net/11427/31357.
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Background Chronic Kidney Disease (CKD), has a high and increasing burden in sub-Saharan Africa. Environmental factors that have been associated to CKD are associated with multiple co-morbidities such as hypertension, diabetes, and HIV. Some genetics factors such APOL1 have been associated with the highest burden of CKD among population of African ancestries. Other emerging genetic factors such as Sickle Cell trait (SCT) have been investigated mostly among African Americans. Sickle Cell trait (SCT) has the highest burden in sub-Saharan Africans, because of a natural selection, attributed to its protective advantages against the severest form of Malaria, caused by Plasmodium falciparum. Many studies showed that SCT has an impact on the normal functioning of the kidneys among African Americans with some studies indicating significant association between SCT and CKD. However, no study has been reported from Sub-Saharan Africa, where most SCT carrier reside. Moreover, there are multiple other loci and variants in the genome that have been associated with CKD in many populations, and that are used for Polygenic Risk Score (PRS) models but have not been explored in populations living in Africa. Aims This project aimed to study in a sub-Saharan African cohort, the association between 1) Sickle cell trait (SCT) with Chronic Kidney disease (CKD), and 2) the association of CKD with 29 targeted single nucleotide polymorphisms (SNPs) identified in multiple Genome-Wide Association studies (GWAS). Methods Patients and controls: 300 Cameroonian adult participants were included: 150 CKD cases and 150 non-CKD age, sex, and comorbidities matched controls. Molecular methods: SCT heterozygosity was determined by RFLP-PCR using the restriction enzyme DdeI. A total of 29 targeted SNPs was genotyped using MassArray and TaqMan techniques, followed by Sanger sequencing in a subset of samples. 11 Statistical Analysis: Descriptive statistics and logistic regression, and Fisher exact test were used. Functional pathway analysis: following the identification SNPs with significant association with CKD, we performed functional pathway test using the Linux programme Cytoscape. Results The mean age of cases was 53 years (range 46-55 years), with 43% that were female; there were no age and sex significant differences with controls. We identified, an expected, association between CKD and various co-morbidities, demographic and anthropometric variables: hypertension (p value = 5.16X10-9 ), HIV (p value = 2.68x10- 9 ), diabetes (p value = 7.12X10-7 ), BMI (p value = 4.58X10-8 ) and age (p value = 4.5X10-8 ). HbAS carrier status was significantly associated CKD (p value= 4.3X10-9 ; Odds Ratio:7.05). Only three targeted SNPs (3/29) previously associated with CKD in GWAS among African Americans, European and Asian population, were significantly associated with CKD among this group of Cameroonians (KBTBD2 rs3750082, PTPRO rs7956634 and LPR2 rs4667594 with p values of 0.02335, 0.0408 and 0.0398). Genes protein-protein interactions analysis identified the two key functional pathways and one network cluster that could play a crucial role in kidney dysfunctions. Lastly, we distinguished that HbS carrier state doesn’t influence the relationship between APOL1 G1/G2 risk alleles and CKD (p value = 0.5725) in this group from subSaharan Africans. Conclusion and perspectives Our study illustrates a strong association between SCT and CKD, an important discovery that will have a major implication in preventative medicine policies and practices in both sub-Saharan African where there is a very high prevalence of SCT. The data also has global resonance, with the projected increase in the prevalence of 12 individual with SCT, due to migration and the improve life expectancy and genetic fitness of people living with both SCT and SCD. We identified a relatively low proportion of (3/29) of target SNPs positively associated with CKD among this group of Cameroonians. The study illustrates that the vast majority of targeted SNPs associated with CKD in GWAS studies in multiple populations including African American, Europeans, and Asians, are not relevant for sub-Saharan Africans, indicating the urgent need to include diverse populations, specifically those living in Africa. Therefore, the data support the possible bias in currently available Polygenic Risk Score generated from GWAS data, where population from sub-Saharan Africa are largely underrepresented. The data further indicate that there is potential to discover new loci associated with CKD when investigating populations of African ancestry living in Africa.
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Pecoraro, Carlo <1986>. "Global Population Genomic Structure and Life History Trait Analysis of Yellowfin Tuna (Thunnus Albacares)." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amsdottorato.unibo.it/7537/1/Pecoraro_Carlo_tesi.pdf.
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Yellowfin tuna (Thunnus albacares; YFT) represents one of the most important seafood commodities in the world. The rationale of this Ph.D. project was identified by prioritizing key issues as objectives for contributing to the conservation of YFT and helping to develop a more realistic stock assessment and sustainable management of this species. Specifically, in this work the current mismatch between the biology and/or ecology and the realized management strategies was highlighted, putting particular emphasis on YFT population structure, which is currently characterized by a high degree of uncertainty at both local and global scale. This general pattern was confirmed by the results obtained using a panel of microsatellite loci, which cannot reject the null hypothesis of the existence of only one panmictic population at the global scale. On the contrary, the access to more powerful and cost effective genetic tools would represent the first step for resolving YFT population structure at both global and local scale. After having evaluated the efficiency and usefulness of 2b-RAD genotyping technique for investigating population genetic structure in highly migratory fish species, a panel of 972 SNPs (Single Nucleotide Polymorphisms) was generated. Using this panel, three distinct populations were identified in the Atlantic, Indian and Pacific Oceans. Additionally, it was possible to define a subset of 33 outlier loci putatively under selection to delineate and separate sub-populations within both the Atlantic and the Pacific Oceans (following an east-west division). Finally, it was emphasized for the first time that in the Atlantic Ocean larger YFT females allocate a greater fraction of surplus energy to egg production than smaller ones, improving noticeably the spawning quality. This result sheds light on the important contribution that larger and most experienced spawners have for the YFT productivity.
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Pecoraro, Carlo <1986>. "Global Population Genomic Structure and Life History Trait Analysis of Yellowfin Tuna (Thunnus Albacares)." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amsdottorato.unibo.it/7537/.
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Yellowfin tuna (Thunnus albacares; YFT) represents one of the most important seafood commodities in the world. The rationale of this Ph.D. project was identified by prioritizing key issues as objectives for contributing to the conservation of YFT and helping to develop a more realistic stock assessment and sustainable management of this species. Specifically, in this work the current mismatch between the biology and/or ecology and the realized management strategies was highlighted, putting particular emphasis on YFT population structure, which is currently characterized by a high degree of uncertainty at both local and global scale. This general pattern was confirmed by the results obtained using a panel of microsatellite loci, which cannot reject the null hypothesis of the existence of only one panmictic population at the global scale. On the contrary, the access to more powerful and cost effective genetic tools would represent the first step for resolving YFT population structure at both global and local scale. After having evaluated the efficiency and usefulness of 2b-RAD genotyping technique for investigating population genetic structure in highly migratory fish species, a panel of 972 SNPs (Single Nucleotide Polymorphisms) was generated. Using this panel, three distinct populations were identified in the Atlantic, Indian and Pacific Oceans. Additionally, it was possible to define a subset of 33 outlier loci putatively under selection to delineate and separate sub-populations within both the Atlantic and the Pacific Oceans (following an east-west division). Finally, it was emphasized for the first time that in the Atlantic Ocean larger YFT females allocate a greater fraction of surplus energy to egg production than smaller ones, improving noticeably the spawning quality. This result sheds light on the important contribution that larger and most experienced spawners have for the YFT productivity.
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Lin, Meng. "Genetic and genomic studies on wheat pre-harvest sprouting resistance." Diss., Kansas State University, 2016. http://hdl.handle.net/2097/34597.
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Doctor of PhilosophyDepartment of Agronomy
Guihua Bai
Allan K. Fritz
Wheat pre-harvest sprouting (PHS), germination of physiologically matured grains in a wheat spike before harvesting, can cause significant reduction in grain yield and end-use quality. Many quantitative trait loci (QTL) for PHS resistance have been reported in different sources. To determine the genetic architecture of PHS resistance and its relationship with grain color (GC) in US hard winter wheat, a genome-wide association study (GWAS) on both PHS resistance and GC was conducted using in a panel of 185 U.S. elite breeding lines and cultivars and 90K wheat SNP arrrays. PHS resistance was assessed by evaluating sprouting rates in wheat spikes harvested from both greenhouse and field experiments. Thirteen QTLs for PHS resistance were identified on 11 chromosomes in at least two experiments, and the effects of these QTLs varied among different environments. The common QTLs for PHS resistance and GC were identified on the long arms of the chromosome 3A and 3D, indicating pleiotropic effect of the two QTLs. Significant QTLs were also detected on chromosome arms 3AS and 4AL, which were not related to GC, suggesting that it is possible to improve PHS resistance in white wheat. To identify markers closely linked to the 4AL QTL, genotyping-by-sequencing (GBS) technology was used to analyze a population of recombinant inbred lines (RILs) developed from a cross between two parents, “Tutoumai A” and “Siyang 936”, contrasting in 4AL QTL. Several closely linked GBS SNP markers to the 4AL QTL were identified and some of them were coverted to KASP for marker-assisted breeding. To investigate effects of the two non-GC related QTLs on 3AS and 4AL, both QTLs were transferered from “Tutoumai A” and “AUS1408” into a susceptible US hard winter wheat breeding line, NW97S186, through marker-assisted backcrossing using the gene marker TaPHS1 for 3AS QTL and a tightly linked KASP marker we developed for 4AL QTL. The 3AS QTL (TaPHS1) significantly interacted with environments and genetic backgrounds, whereas 4AL QTL (TaMKK3-A) interacted with environments only. The two QTLs showed additive effects on PHS resistance, indicating pyramiding these two QTLs can increase PHS resistance. To improve breeding selection efficiency, genomic prediction using genome-wide markers and marker-based prediction (MBP) using selected trait-linked markers were conducted in the association panel. Among the four genomic prediction methods evaluated, the ridge regression best linear unbiased prediction (rrBLUP) provides the best prediction among the tested methods (rrBLUP, BayesB, BayesC and BayesC0). However, MBP using 11 significant SNPs identified in the association study provides a better prediction than genomic prediction. Therefore, for traits that are controlled by a few major QTLs, MBP may be more effective than genomic selection.
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He, Feng, and 贺峰. "Detection of parent-of-origin effects and association in relation to aquantitative trait." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B44921408.
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Toubiana, William. "Towards an adaptive and genomic understanding of an exaggerated secondary sexual trait in water striders." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEN058/document.
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Les nombreuses différences qui existent entre les organismes illustrent que le processus de variation est un phénomène universel en biologie. Ces variations sont particulièrement observables chez les espèces sexuées, entre mâles et femelles. Comprendre les différents facteurs biologiques, environnementaux et génétiques, à l'origine de ce dimorphisme sexuel est le cœur de mon sujet de thèse. Pour cela, j’ai établi un nouveau modèle d'étude, l’insecte semi-aquatique Microvelia longipes. Ces insectes ont évolué un dimorphisme sexuel spectaculaire où les mâles présentent une croissance extrême et hypervariable spécifiquement au niveau de la troisième paire de pattes. Pour étudier ce phénomène, nous avons, en premier lieu, émis l’hypothèse que cette croissance exagérée était associée à des pressions de sélection sexuelle. Nous avons mis en évidence la présence de compétition intense entre males, qui utilisent leurs pattes arrière comme arme, pour s’accoupler avec les femelles. Les males à pattes plus longues gagnent souvent dans ces combats, expliquant l’importance adaptative de ces pattes exagérées chez les mâles. De plus, nous montrons que l’intensité que mettent les mâles à se battre est associée aux variations de taille de pattes chez les mâles, de la même espèce ou d’espèces différentes. Nous avons également développé un génome et une approche transcriptomique comparant les sexes et les pattes afin d’identifier les gènes responsables de cette croissance exagérée. Ceci a permis de dresser une liste de gènes dont l’expression corrèle avec l’exagération de la croissance des pattes chez les mâles et d’identifier des régions génomiques associées à la sélection sexuelleFrom the DNA molecule to the more complex phenotypes, variation is a universal process in life and living organisms. The innumerable differences that exist between species are probably one of the most manifest examples. Yet, all this diversity would never have occurred in nature without some pre-existing divergence within species. One of the most striking examples of intraspecies variation appears in sexual organisms, between males and females. Understanding the environmental and genetic factors influencing sexual divergence is a longstanding question in evolutionary biology. To this end, I focus here on a new insect model system, Microvelia longipes, which has the particularity to have evolved an extreme case of sexual dimorphism in the rear legs. Males display exaggerated long rear legs compared to females but also an extreme variability in these leg lengths from one male to another. We identified that M. longipes males use their exaggerated legs as weapons during male-male competition. Males with longer legs have more chance to access females on egg-laying sites and therefore increase their reproductive success. Moreover, fitness assays and comparative studies between Microvelia species revealed that the intensity of male competition was associated with the exaggeration and hypervariability of the rear legs in M. longipes males. In a second approach, we studied the developmental and genomic basis of this sexual dimorphism through a comparative transcriptomic analysis and identified genes and genomic regions associated with male exaggerated legs and ultimately with sexual selection. Overall, the integrative approach used in this work allows to establish Microvelia longipes as a promising new model system to study the influence of sexual selection in adaptive evolution
Books on the topic "Genomic trait"
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Fontanesi, Luca, ed. The genetics and genomics of the rabbit. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781780643342.0000.
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Abstract The purpose of the book is to present in one location a comprehensive overview of the progress of genetics in the rabbit, with a modern vision that integrates genomics to obtain a complete picture of the state of the art and of the applications in this species, defined according to the multiple uses and multi-faceted places that this species has in applied and fundamental biology. The 18 chapters cover several fields of genetics and genomics: Chapters 1 and 2 present the rabbit within the evolutionary framework, including the systematics, its domestication and an overview of the genetic resources (breeds and lines) that have been developed after domestication. Chapters 3-5 cover the rabbit genome, cytogenetics and genetic maps and immunogenetics in this species. Chapters 6-8 present the genetics and molecular genetics of coat colours, fibre traits and other morphological traits and defects. Chapters 9-13 cover the genetics of complex traits (disease resistance, growth and meat production traits, reproduction traits), reproduction technologies and genetic improvement in the meat rabbits. Chapters 14-18 present the omics vision, the biotech and biomodelling perspectives and applications of the rabbit. This book is addressed to a broad audience, including students, teachers, researchers, veterinarians and rabbit breeders.
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Lantbruksuniversitet, Sveriges, ed. Genome analysis of quantitative trait loci in the pig. Uppsala: Sveriges Lantbruksuniversitet, 1997.
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Gloyn, Anna L., and Mark I. McCarthy. Genetics in diabetes: Type 2 diabetes and related traits. Basel: Karger, 2014.
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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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Nōrin Suisan Gijutsu Kaigi. Jimukyoku., ed. Yūyō idenshi katsuyō no tame no shokubutsu (ine) dōbutsu genomu kenkyū, ine genomu no jūyō keishitsu kanren idenshi no kinō kaimei =: Functional analysis of genes relevant to agriculturally important traits in rice genome. Tōkyō: Nōrin Suisan Gijutsu Kaigi Jimukyoku, 2009.
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Maroni, Gustavo. Molecular and Genetic Analysis of Human Traits. New York: John Wiley & Sons, Ltd., 2007.
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Nōrin Suisan Gijutsu Kaigi. Jimukyoku., ed. Genomu ikushu ni yoru kōritsuteki hinshu ikusei gijutsu no kaihatsu, QTL idenshi kaiseki no suishin =: Genetic and molecular dissection of quantitative traits in rice. Tōkyō: Nōrin Suisan Gijutsu Kaigi Jimukyoku, 2009.
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Nōrin Suisan Gijutsu Kaigi. Jimukyoku., ed. Genomu ikushu ni yoru kōritsuteki hinshu ikusei gijutsu no kaihatsu, QTL idenshi kaiseki no suishin =: Genetic and molecular dissection of quantitative traits in rice. Tōkyō: Nōrin Suisan Gijutsu Kaigi Jimukyoku, 2009.
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Saunak, Sen, and SpringerLink (Online service), eds. A Guide to QTL Mapping with R/qtl. New York, NY: Springer-Verlag New York, 2009.
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Genomic Selection in Animals. Wiley-Blackwell, 2016.
Find full textBook chapters on the topic "Genomic trait"
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Montesinos López, Osval Antonio, Abelardo Montesinos López, and Jose Crossa. "Linear Mixed Models." In Multivariate Statistical Machine Learning Methods for Genomic Prediction, 141–70. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89010-0_5.
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AbstractThe linear mixed model framework is explained in detail in this chapter. We explore three methods of parameter estimation (maximum likelihood, EM algorithm, and REML) and illustrate how genomic-enabled predictions are performed under this framework. We illustrate the use of linear mixed models by using the predictor several components such as environments, genotypes, and genotype × environment interaction. Also, the linear mixed model is illustrated under a multi-trait framework that is important in the prediction performance when the degree of correlation between traits is moderate or large. We illustrate the use of single-trait and multi-trait linear mixed models and provide the R codes for performing the analyses.
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Qiu, Zhixu, Yunjia Tang, and Chuang Ma. "An Effective Strategy for Trait Combinations in Multiple-Trait Genomic Selection." In Intelligent Computing Theories and Application, 230–39. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63312-1_21.
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Crossa, José, J. Jesús Cerón-Rojas, Johannes W. R. Martini, Giovanny Covarrubias-Pazaran, Gregorio Alvarado, Fernando H. Toledo, and Velu Govindan. "Theory and Practice of Phenotypic and Genomic Selection Indices." In Wheat Improvement, 593–616. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90673-3_32.
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AbstractThe plant net genetic merit is a linear combination of trait breeding values weighted by its respective economic weights whereas a linear selection index (LSI) is a linear combination of phenotypic or genomic estimated breeding values (GEBV) which is used to predict the net genetic merit of candidates for selection. Because economic values are difficult to assign, some authors developed economic weight-free LSI. The economic weights LSI are associated with linear regression theory, while the economic weight-free LSI is associated with canonical correlation theory. Both LSI can be unconstrained or constrained. Constrained LSI imposes restrictions on the expected genetic gain per trait to make some traits change their mean values based on a predetermined level, while the rest of the traits change their values without restriction. This work is geared towards plant breeders and researchers interested in LSI theory and practice in the context of wheat breeding. We provide the phenotypic and genomic unconstrained and constrained LSI, which together cover the theoretical and practical cornerstone of the single-stage LSI theory in plant breeding. Our main goal is to offer researchers a starting point for understanding the core tenets of LSI theory in plant selection.
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Montesinos López, Osval Antonio, Abelardo Montesinos López, and Jose Crossa. "Bayesian Genomic Linear Regression." In Multivariate Statistical Machine Learning Methods for Genomic Prediction, 171–208. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-89010-0_6.
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AbstractThe Bayesian paradigm for parameter estimation is introduced and linked to the main problem of genomic-enabled prediction to predict the trait of interest of the non-phenotyped individuals from genotypic information, environment variables, or other information (covariates). In this situation, a convenient practice is to include the individuals to be predicted in the posterior distribution to be sampled. We explained how the Bayesian Ridge regression method is derived and exemplified with data from plant breeding genomic selection. Other Bayesian methods (Bayes A, Bayes B, Bayes C, and Bayesian Lasso) were also described and exemplified for genome-based prediction. The chapter presented several examples that were implemented in the Bayesian generalized linear regression (BGLR) library for continuous response variables. The predictor under all these Bayesian methods includes main effects (of environments and genotypes) as well as interaction terms related to genotype × environment interaction.
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Sukumaran, Sivakumar, Greg Rebetzke, Ian Mackay, Alison R. Bentley, and Matthew P. Reynolds. "Pre-breeding Strategies." In Wheat Improvement, 451–69. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-90673-3_25.
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AbstractIn general terms, pre-breeding links needed traits to new varieties and encompasses activities from discovery research, exploration of gene banks, phenomics, genomics and breeding. How does pre-breeding given its importance differ from varietal-based breeding? Why is pre-breeding important? Pre-breeding identifies trait or trait combinations to help boost yield, protect it from biotic or abiotic stress, and enhance nutritional or quality characteristics of grain. Sources of new traits/alleles are typically found in germplasm banks, and include the following categories of ‘exotic’ material: obsolete varieties, landraces, products of interspecific hybridization within the Triticeae such as chromosome translocation lines, primary synthetic genotypes and their derivatives, and related species mainly from the primary or secondary gene pools (Genus: Triticum and Aegilops). Genetic and/or phenotyping tools are used to incorporate novel alleles/traits into elite varieties. While pre-breeding is mainly associated with use of exotics, unconventional crosses or selection methodologies aimed to accumulate novel combinations of alleles or traits into good genetic backgrounds may also be considered pre-breeding. In the current chapter, we focus on pre-breeding involving research-based screening of genetic resources, strategic crossing to combine complementary traits/alleles and progeny selection using phenomic and genomic selection, aiming to bring new functional diversity into use for development of elite cultivars.
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Mukhopadhyay, CS, and Bhawanpreet Kaur. "Applications of Tag-SNPs in Quantitative Trait Loci (QTL) Identification." In Genomic, Proteomics, and Biotechnology, 89–100. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003220831-6.
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Shi, Shaolei, Zhe Zhang, Bingjie Li, Shengli Zhang, and Lingzhao Fang. "Incorporation of Trait-Specific Genetic Information into Genomic Prediction Models." In Methods in Molecular Biology, 329–40. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2205-6_11.
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Morota, Gota, Diego Jarquin, Malachy T. Campbell, and Hiroyoshi Iwata. "Statistical Methods for the Quantitative Genetic Analysis of High-Throughput Phenotyping Data." In Methods in Molecular Biology, 269–96. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2537-8_21.
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AbstractThe advent of plant phenomics, coupled with the wealth of genotypic data generated by next-generation sequencing technologies, provides exciting new resources for investigations into and improvement of complex traits. However, these new technologies also bring new challenges in quantitative genetics, namely, a need for the development of robust frameworks that can accommodate these high-dimensional data. In this chapter, we describe methods for the statistical analysis of high-throughput phenotyping (HTP) data with the goal of enhancing the prediction accuracy of genomic selection (GS). Following the Introduction in Sec. 1, Sec. 2 discusses field-based HTP, including the use of unoccupied aerial vehicles and light detection and ranging, as well as how we can achieve increased genetic gain by utilizing image data derived from HTP. Section 3 considers extending commonly used GS models to integrate HTP data as covariates associated with the principal trait response, such as yield. Particular focus is placed on single-trait, multi-trait, and genotype by environment interaction models. One unique aspect of HTP data is that phenomics platforms often produce large-scale data with high spatial and temporal resolution for capturing dynamic growth, development, and stress responses. Section 4 discusses the utility of a random regression model for performing longitudinal modeling. The chapter concludes with a discussion of some standing issues.
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Govindaraj, Mahalingam, Mahesh Pujar, Rakesh Srivastava, S. K. Gupta, and Wolfgang H. Pfeiffer. "Genetic Biofortification of Pearl Millet: Trait Priority, Breeding and Genomic Progress." In Pearl Millet in the 21st Century, 221–46. Singapore: Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-5890-0_9.
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Calayugan, Mark Ian C., B. P. Mallikarjuna Swamy, Chau Thanh Nha, Alvin D. Palanog, Partha S. Biswas, Gwen Iris Descalsota-Empleo, Yin Myat Myat Min, and Mary Ann Inabangan-Asilo. "Zinc-Biofortified Rice: A Sustainable Food-Based Product for Fighting Zinc Malnutrition." In Rice Improvement, 449–70. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66530-2_13.
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AbstractThe lack of dietary diversity among poor communities has led to nutritional consequences, particularly zinc deficiency. An adequate intake of mineral- and vitamin-rich food is necessary for achieving and maintaining good health. Zinc is one of the micronutrients considered essential to improve human health and decrease the risk of malnutrition. Biofortification of rice through breeding is a cost-effective and sustainable strategy to solve micronutrient malnutrition. The Biofortification Priority Index prepared by HarvestPlus clearly identified several countries in Asia with an immediate need for Zn biofortification. The International Rice Research Institute (IRRI) and its national partners in target countries are making efforts to develop Zn-biofortified rice varieties. The first set of high-Zn rice varieties has been released for commercial cultivation in Bangladesh, India, the Philippines, and Indonesia. Efforts have begun to mainstream grain Zn to ensure that the Zn trait becomes an integral part of future varieties. Huge scope exists to apply advanced genomics technologies such as genomic selection and genome editing to speed up high-Zn varietal development. An efficient rice value chain for Zn-biofortified varieties, quality control, and promotion are essential for successful adoption and consumption. The development of next-generation high-Zn rice varieties with higher grain-Zn content, stacking of multiple nutrients, along with good grain quality and acceptable agronomic traits has to be fast-tracked. Healthier rice has a large demand from all stakeholders, so we need to keep up the pace of developing nutritious rice to meet the demand and to achieve nutritional security.
Conference papers on the topic "Genomic trait"
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Beyer, Andreas, Silpa Suthram, and Trey Ideker. "Uncovering Regulatory Pathways with Expression Quantitative Trait Loci." In 2007 IEEE International Workshop on Genomic Signal Processing and Statistics. IEEE, 2007. http://dx.doi.org/10.1109/gensips.2007.4365837.
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Schmidtmann, C., D. Segelke, J. Bennewitz, J. Tetens, and G. Thaller. "284. Considering chromosomal trait correlations improves accuracy of genomic prediction." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_284.
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Meyer, K. "361. Accounting for trait-specific genomic and residual polygenic covariances in multivariate single-step genomic evaluation." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_361.
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Akanno, E. C., D. M. Thekkoot, C. Zhang, C. Bierman, G. Plastow, and R. A. Kemp. "300. Multi-trait genomic estimation of genetic parameters for growth and carcass traits of Duroc pigs." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_300.
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Mamani, G. C., B. F. Santana, and D. Jarquin. "809. Assessing genomic prediction of economic trait in alpacas: a simulation study." In World Congress on Genetics Applied to Livestock Production. The Netherlands: Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-940-4_809.
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COMERON, JOSEP M., MARTIN KREITMAN, and FRANCISCO M. DE LA VEGA. "ON THE POWER TO DETECT SNP/PHENOTYPE ASSOCIATION IN CANDIDATE QUANTITATIVE TRAIT LOCI GENOMIC REGIONS: A SIMULATION STUDY." In Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776303_0045.
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"Marker-trait associations for agronomic traits in soybean harvested in Kazakhstan." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-213.
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Verweij, C. L., R. Quadt, E. Briët, and H. Pannekoek. "TWO VON WILLEBRAND FACTOR (vWF) GENE POLYMORPHISMS SEGREGATE WITH VON WILLEBRAND'S DISEASE (vWD) TYPE IIA: ASSIGNMENT OF THE DEFECTIVE GENE LOCUS IN vWD TYPE IIA." In XIth International Congress on Thrombosis and Haemostasis. Schattauer GmbH, 1987. http://dx.doi.org/10.1055/s-0038-1644646.
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Patients with autosomal, dominant von Willebrand's disease (vWD) type IIA display a decreasedristocetin cofactor activity and lack the large and intermediate size von Willebrand factor (vWF) multimers. As yet the cause for this abnormal vWF protein is not known. In this study we determined whether vWD type IIA is due to a mutation in the vWF gene or by a defect in another gene involved, in for example, vWF processing.Restriction fragment-length polymorphisms (RFLP's), using the enzymes BgIII and XbaI in conjunction with human vWF cDNA probes, have been described. Restriction endonuclease analysis of genomic vWF DNA revealed that these genetic marker are located within the vWF gene. The vWF gene was determined to comprise about 160 kb and harbors at least 20 exons. The RFLP's were applied to study the segregation of alleles associated withvWD type IIA in a comprehensive, affected family. It is demonstrated that both RFLP's are completely linked with the vWD type-IIA trait. From this finding, we conclude that the defect, causing the vWD type IIA, is most likely due to a mutation in the vWF gene and not to a mutation in another gene involved in, for example, post-translational processing of the vWF protein.
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"Marker-trait associations for barley grain quality traits identified in Karaganda and Kostanay regions using GWAS." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Novosibirsk ICG SB RAS 2021, 2021. http://dx.doi.org/10.18699/plantgen2021-063.
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"Association mapping of quantitative trait loci for agronomic traits in spring wheat collection tested under two water regimes in Northern Kazakhstan." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Novosibirsk ICG SB RAS 2021, 2021. http://dx.doi.org/10.18699/plantgen2021-007.
Full textReports on the topic "Genomic trait"
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Sherman, A., D. N. Kuhn, Y. Cohen, R. Ophir, and R. Goenaga. Exploring the polyembryonic seed trait in mango as a basis for a biotechnology platform for fruit tree crops. Israel: United States-Israel Binational Agricultural Research and Development Fund, 2021. http://dx.doi.org/10.32747/2021.8134176.bard.
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Mango is one of the most important fruit crops. However, the biology of this fruit tree is under studied. The lack of genetic and genomic resources has limited progress in mango research and breeding. Several research groups have recently started developing genomic tools for mango by creating transcriptome and genomic data. Sexual reproduction in plants is the main pathway for the creation of new genetic combinations. In modern agriculture, breeders exploit the genetic diversity generated through sexual reproduction to develop elite cultivars; however, these cultivars require genetic stabilization before they are suitable for mass propagation for uniform crop production. In heterozygous plants such as fruit trees, vegetative propagation (cloning) is the primary path for the propagation of genetically uniform plants. Another natural plant mechanism that can create genetically uniform plants (clones) is apomixes. Apomixis is defined as asexual reproduction through seeds that lead to the production of clonal progeny whose genotype is identical to that of the mother plant. In fruit crops like citrus and mango, sporophytic apomixes result in polyembryony, where seeds contain multiple embryos, one of which is sexually originated, and the others are clones of the mother tree. As part of this research, the reference genome of mango was established as a basic platform for mango breeding and research. It was used to map two important mango traits fruit size and polyembryony. The draft genome 'Tommy Atkins' sequence was generated using NRGene de-novo Magic on high molecular weight DNA of 'Tommy Atkins,' supplemented by 10X Genomics long read sequencing to improve the initial assembly. The final 'Tommy Atkins' genome assembly was a consensus sequence that included 20 pseudomolecules representing the 20 chromosomes of mango. The availability of a genome enables the genetic dissection of important traits. We demonstrated the utility of the genome assembly and the 'Tommy Atkins' x 'Kensington Pride' map by analyzing fruit weight phenotypic data and identifying two QTLs for this trait.
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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 <10²⁰ 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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Weller, Joel I., Ignacy Misztal, and Micha Ron. Optimization of methodology for genomic selection of moderate and large dairy cattle populations. United States Department of Agriculture, March 2015. http://dx.doi.org/10.32747/2015.7594404.bard.
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The main objectives of this research was to detect the specific polymorphisms responsible for observed quantitative trait loci and develop optimal strategies for genomic evaluations and selection for moderate (Israel) and large (US) dairy cattle populations. A joint evaluation using all phenotypic, pedigree, and genomic data is the optimal strategy. The specific objectives were: 1) to apply strategies for determination of the causative polymorphisms based on the “a posteriori granddaughter design” (APGD), 2) to develop methods to derive unbiased estimates of gene effects derived from SNP chips analyses, 3) to derive optimal single-stage methods to estimate breeding values of animals based on marker, phenotypic and pedigree data, 4) to extend these methods to multi-trait genetic evaluations and 5) to evaluate the results of long-term genomic selection, as compared to traditional selection. Nearly all of these objectives were met. The major achievements were: The APGD and the modified granddaughter designs were applied to the US Holstein population, and regions harboring segregating quantitative trait loci (QTL) were identified for all economic traits of interest. The APGD was able to find segregating QTL for all the economic traits analyzed, and confidence intervals for QTL location ranged from ~5 to 35 million base pairs. Genomic estimated breeding values (GEBV) for milk production traits in the Israeli Holstein population were computed by the single-step method and compared to results for the two-step method. The single-step method was extended to derive GEBV for multi-parity evaluation. Long-term analysis of genomic selection demonstrated that inclusion of pedigree data from previous generations may result in less accurate GEBV. Major conclusions are: Predictions using single-step genomic best linear unbiased prediction (GBLUP) were the least biased, and that method appears to be the best tool for genomic evaluation of a small population, as it automatically accounts for parental index and allows for inclusion of female genomic information without additional steps. None of the methods applied to the Israeli Holstein population were able to derive GEBV for young bulls that were significantly better than parent averages. Thus we confirm previous studies that the main limiting factor for the accuracy of GEBV is the number of bulls with genotypes and progeny tests. Although 36 of the grandsires included in the APGD were genotyped for the BovineHDBeadChip, which includes 777,000 SNPs, we were not able to determine the causative polymorphism for any of the detected QTL. The number of valid unique markers on the BovineHDBeadChip is not sufficient for a reasonable probability to find the causative polymorphisms. Complete resequencing of the genome of approximately 50 bulls will be required, but this could not be accomplished within the framework of the current project due to funding constraints. Inclusion of pedigree data from older generations in the derivation of GEBV may result is less accurate evaluations.
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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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Dechow, Chad Daniel, M. Cohen-Zinder, Morris Soller, Y. Tzfati, A. Shabtay, E. Lipkin, T. Ott, and W. Liu. Genotypes and phenotypes of telomere length in Holstein cattle, actors or reporters. Israel: United States-Israel Binational Agricultural Research and Development Fund, 2020. http://dx.doi.org/10.32747/2020.8134156.bard.
Full textAbstract:
Selection programs aiming at improving health and survival in cattle are complicated by low heritability estimates, the fact that true herd life and carcass quality is not known until the end of an animal's life, and that many health conditions manifest late in life. Young animals are now heavily favored in breeding programs because low generation intervals accelerate the rate of genetic progress, which means selection decisions must be made before phenotypic observation of health and survival is feasible. Moreover, profitability is compromised when livestock producers raise animals that fail to produce due to health failure or that do not meet quality standards. Telomere length (TL) was hypothesized as a biomarker that could be recorded early in life, be associated with health and survival, and have higher heritability than other measures of health. Thus, our research aims were to: 1, determine associations of TL with health, wellbeing and production in Holsteins raised for dairy or beef purposes; 2, determine TL heritability, genetic variance, and genetic correlations with cow health and performance; and 3, map quantitative trait loci affecting TL and provide TL genomic predictions to industry partners and breeders. There were not significant changes made to the research plan during the project, but the timeline of the project was not met. Laboratory processing of samples was significantly delayed due to Covid along with some sample collection. TL measurements from >1100 animals across the US and Israel are available to date. TL declines modestly with age, in agreement with observations from other species. A genomic analysis was conducted using a single-step approach and TL had a moderate heritability estimate of 20% across age groups. The initial genome-wide association-analysis indicated that TL is a quantitative trait whose expression is influenced by effects across the genome. Moreover, there is a strong association of calf and dam TL at birth. Genetic relationships with health and survival were ascertained through correlations of genomic estimated breeding values (gEBV) for TL with gEBV for other traits routinely recording in national genetic evaluations. Higher TL is genetically associated with longer herd-life, a greater likelihood that cows will avoid premature on-farm death, and reduced disease incidence. The relationship appeared to be strongest when TL was measured during the first two years of life. Based on genotyping different cell types, there was evidence that maternal and colostral derived cells are present in newborns, which could bias TL measurements during the first weeks of life to a small degree. The implications of this research are that TL is a promising trait to include in multiple trait selection programs because it is heritable, available early in life, and correlated with longevity and health. Our TL reference population is currently being expanded, and genomic estimated breeding values will be disseminated to industry partners upon completion of the reference population so that they can evaluate the utility of incorporating TL into their breeding programs.
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Fridman, Eyal, Jianming Yu, and Rivka Elbaum. Combining diversity within Sorghum bicolor for genomic and fine mapping of intra-allelic interactions underlying heterosis. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7597925.bard.
Full textAbstract:
Heterosis, the enigmatic phenomenon in which whole genome heterozygous hybrids demonstrate superior fitness compared to their homozygous parents, is the main cornerstone of modern crop plant breeding. One explanation for this non-additive inheritance of hybrids is interaction of alleles within the same locus. This proposal aims at screening, identifying and investigating heterosis trait loci (HTL) for different yield traits by implementing a novel integrated mapping approach in Sorghum bicolor as a model for other crop plants. Originally, the general goal of this research was to perform a genetic dissection of heterosis in a diallel built from a set of Sorghum bicolor inbred lines. This was conducted by implementing a novel computational algorithm which aims at associating between specific heterozygosity found among hybrids with heterotic variation for different agronomic traits. The initial goals of the research are: (i) Perform genotype by sequencing (GBS) of the founder lines (ii) To evaluate the heterotic variation found in the diallel by performing field trails and measurements in the field (iii) To perform QTL analysis for identifying heterotic trait loci (HTL) (iv) to validate candidate HTL by testing the quantitative mode of inheritance in F2 populations, and (v) To identify candidate HTL in NAM founder lines and fine map these loci by test-cross selected RIL derived from these founders. The genetic mapping was initially achieved with app. 100 SSR markers, and later the founder lines were genotyped by sequencing. In addition to the original proposed research we have added two additional populations that were utilized to further develop the HTL mapping approach; (1) A diallel of budding yeast (Saccharomyces cerevisiae) that was tested for heterosis of doubling time, and (2) a recombinant inbred line population of Sorghum bicolor that allowed testing in the field and in more depth the contribution of heterosis to plant height, as well as to achieve novel simulation for predicting dominant and additive effects in tightly linked loci on pseudooverdominance. There are several conclusions relevant to crop plants in general and to sorghum breeding and biology in particular: (i) heterosis for reproductive (1), vegetative (2) and metabolic phenotypes is predominantly achieved via dominance complementation. (ii) most loci that seems to be inherited as overdominant are in fact achieving superior phenotype of the heterozygous due to linkage in repulsion, namely by pseudooverdominant mechanism. Our computer simulations show that such repulsion linkage could influence QTL detection and estimation of effect in segregating populations. (iii) A new height QTL (qHT7.1) was identified near the genomic region harboring the known auxin transporter Dw3 in sorghum, and its genetic dissection in RIL population demonstrated that it affects both the upper and lower parts of the plant, whereas Dw3 affects only the part below the flag leaf. (iv) HTL mapping for grain nitrogen content in sorghum grains has identified several candidate genes that regulate this trait, including several putative nitrate transporters and a transcription factor belonging to the no-apical meristem (NAC)-like large gene family. This activity was combined with another BARD-funded project in which several de-novo mutants in this gene were identified for functional analysis.
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Seroussi, E., L. Ma, and G. Liu. Genetic analyses of recombination and PRDM9 alleles and their implications in dairy cattle breeding. Israel: United States-Israel Binational Agricultural Research and Development Fund, 2020. http://dx.doi.org/10.32747/2020.8134158.bard.
Full textAbstract:
Meiotic recombination is one of the important phenomena contributing to gamete genome diversity. However, it is not well studied in livestock including cattle. The general objectives of this project were to perform genetic analyses of recombination and PRDM9 alleles and study their implications in dairy cattle breeding. The specific objectives were: 1. Analyze variation in recombination across individuals, breeds, and environments; 1.1.Construct individual-level recombination maps; 1.2.Compare recombination features between bulls held under different environmental conditions in US and Israeli; 2. Examine genetic basis of recombination variation in cattle; 2.1.Characterize PRDM9 alleles and their impacts on total and locus-specific recombination features; 2.2.Validate pedigree-based recombination maps using single sperm sequencing and typing; 3. Investigate the impacts of recombination on dairy cattle breeding; 3.1.Evaluate correlation between recombination and dairy production and health traits; 3.2.Evaluate the benefits of incorporating recombination as novel quantitative trait into genomic selection scheme.
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Abbott, Albert G., Doron Holland, Douglas Bielenberg, and Gregory Reighard. Structural and Functional Genomic Approaches for Marking and Identifying Genes that Control Chilling Requirement in Apricot and Peach Trees. United States Department of Agriculture, September 2009. http://dx.doi.org/10.32747/2009.7591742.bard.
Full textAbstract:
Structural and functional genomic approaches for marking and identifying genes that control chilling requirement in apricot and peach trees. Specific aims: 1) Identify and characterize the genetic nature of chilling requirement for flowering and dormancy break of vegetative shoots in Prunusgermplasm through the utilization of existing apricot (NeweYa'ar Research Center, ARO) and peach (Clemson University) genetic mapping populations; 2) Use molecular genetic mapping techniques to identify markers flanking genomic regions controlling chilling; 3) Comparatively map the regions controlling chilling requirement in apricot and peach and locate important genomic regions influencing chilling requirement on the Prunus functional genomic database as an initial step for identification of candidate genes; 4) Develop from the functional genomics database a set of markers facilitating the development of cultivars with optimized chilling requirements for improved and sustained fruit production in warm-winter environments. Dormant apricot (prunus armeniaca L.) and peach [Prunus persica (L.) Batsch] trees require sustained exposure to low, near freezing, temperatures before vigorous floral and vegetative bud break is possible after the resumption of warm temperatures in the spring. The duration of chilling required (the chilling requirement, CR) is determined by the climatic adaptation of the particular cultivar, thus limiting its geographic distribution. This limitation is particularly evident when attempting to introduce superior cultivars to regions with very warm winter temperatures, such as Israel and the coastal southern United States. The physiological mechanism of CR is not understood and although breeding programs deliberately manipulate CR in apricot and peach crosses, robust closely associated markers to the trait are currently not available. We used segregating populations of apricot (100 Fl individuals, NeweYa'ar Research Center, ARO) and peach (378 F2 individuals, Clemson University) to discover several discreet genomic loci that regulate CR and blooming date. We used the extensive genomic/genetic resources available for Prunus to successfully combine our apricot and peach genetic data and identify five QTL with strong effects that are conserved between species as well as several QTL that are unique to each species. We have identified markers in the key major QTL regions for testing in breeding programs which we are carrying out currently; we have identified an initial set of candidate genes using the peach physical/transcriptome map and whole peach genome sequences and we are testing these currently to identify key target genes for manipulation in breeding programs. Our collaborative work to date has demonstrated the following: 1) CR in peach and apricot is predominantly controlled by a limited number ofQTL loci, seven detected in a peach F2 derived map comprising 65% of the character and 12 in an apricot Fl map comprising 71.6% and 55.6% of the trait in the Perfection and A. 1740 parental maps, respectively and that peach and apricot appear in our initial maps to share five genomic intervals containing potentially common QTL. 2) Application of common anchor markers of the Prunus/peach, physical/genetic map resources has allowed us not only to identify the shared intervals but also to have immediately available some putative candidate gene information from these intervals, the EVG region on LG1 in peach the TALY 1 region in apricot on LG2 in peach; and several others involved in vernalization pathways (LGI and LG7). 3) Mapped BACcontigs are easily defined from the complete physical map resources in peach through the common SSR markers that anchor our CR maps in the two species, 4) Sequences of BACs in these regions can be easily mined for additional polymorphic markers to use in MAS applications.
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Ozias-Akins, P., and R. Hovav. molecular dissection of the crop maturation trait in peanut. Israel: United States-Israel Binational Agricultural Research and Development Fund, 2020. http://dx.doi.org/10.32747/2020.8134157.bard.
Full textAbstract:
Crop maturation is one of the most recognized characteristics of peanut, and it is crucial for adaptability and yield. However, not much is known regarding its genetic and molecular control. The goals of this project were to study the molecular-genetic components that control crop maturation in peanut and identify candidate genes. Crop maturation was studied directly by phenotyping the maturity level or through other component traits such as flowering pattern and branching habit. Six different RIL populations (HH, RR, CC, FNC, TGT and FLIC) were used for the genetic analysis. In total, 14 QTLs were found for maturity level. The phenotypic explanation values ranged in 5.3%-18.6%. Common QTL were found between maturity level and harvest index (in RR and CC populations), branching habit (in HH population), flowering pattern/branching rate (in CC and TGT populations) and pod size (in CC population). Further investigations were done to define genes that control maturity level and the component traits. A map-based cloning approach was used to identify a major candidate gene for branching habit - a novel AhMADS-box gene (AhMADS). AhMADS was mainly expressed in the lateral shoot, the organ in which the difference between branching habit occurs. Sequence alignment analysis found SNPs in AhMADS that cause to exon/intron splicing alterations. Overexpression study of AhMADs-box in tobacco under 35S control revealed one line with a spreading-like lateral shoot indicating that AhMADS may be the causing effect of BH and therefore indirectly controls maturity level. In addition, several candidate genes were defined that may control flowering pattern. An RNA expression study was performed on two parental lines, Tifrunner and GT-C20, identifying four candidate genes in the flowering regulatory pathway that were down-regulated at the mainstem (non-flowering) compared to the first (flowering) shoot, indicating their influence on flowering pattern. Also, another candidate gene was identified, Terminal Flowering 1-like (AhTFL1), which was located within a small segment in chromosome B02. A 1492 bp deletion was found in AhTFL1 that completely co-segregates with the flowering pattern phenotype in the CC population and two independent EMS-mutagenized M2 families. AhTFL1 was significantly less expressed in flowering than non-flowering branches. Finally, a field trial showed that an EMS line (B78) mutagenized in AhTFL1 is ~18% days earlier than the control (Hanoch). In conclusion, our study revealed new insights into the molecular basis for the fundamentally important crop maturity trait in peanut. The results generated new information and materials that will promote informed targeting of peanut idiotypes by indirect selection and genomic breeding approaches.
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Grumet, R., J. Burger, Y. Tadmor, A. Gur, C. Barry, A. Schäffer, and M. Petreikov. Cucumis fruit surface biology: Genetic analysis of fruit exocarp features in melon (C. melo) and cucumber (C. sativus). Israel: United States-Israel Binational Agricultural Research and Development Fund, 2020. http://dx.doi.org/10.32747/2020.8134155.bard.
Full textAbstract:
The fruit surface (exocarp) is a unique tissue with multiple roles influencing fruit growth and development, disease susceptibility, crop yield, post-harvest treatments, shipping and storage quality, and food safety. Furthermore, highly visible exocarp traits are the consumer's first exposure to the fruit, serving to identify fruit type, variety, attractiveness, and market value. Cucurbit fruit, including the closely related Cucumis species, melon (C. melo) and cucumber (C. sativus), exhibit tremendous diversity for fruit surface properties that are not present in model species. In this project, we identified genetic factors influencing Cucumis fruit surface morphology with respect to important quality determinants such as exocarp and flesh color, cuticle deposition, and surface netting. We employed a combination of approaches including: genome-wide association studies (GWAS) utilizing an extensive melon population and the U.S. Plant Introduction (PI) collection for cucumber to identify genomic regions associated with natural variation in fruit surface traits; bulked segregant RNA-seq (BSR-seq) analysis of bi-parental F2:3 or RIL (recombinant inbred line) populations to genomic regions and candidate genes segregating for fruit surface traits; and comparison of syntenic genomic regions and identification of homologous candidate genes. Candidate genes were examined for sequence and/or expression differences during fruit development that correspond with phenotypic differences. Primary outcomes of the work included identification of candidate genes influencing cuticle deposition, epidermal cell structure, surface netting, and intensity of rind and flesh color. Parallel studies identified mutations within the cucumber and melon homologs of the transcription factor WIN1 (WAX INDUCER1) as a significant factor influencing these surface properties. Additional QTL (quantitative trait loci) were identified in both species, and candidate genes in melon include a novel beta-glucosidase involved in lignin production and an integral membrane protein potentially involved in cuticle metabolism. Genetic resources and biochemical approaches have been developed to study cuticle and wax deposition in both species: segregating populations of melon were developed and sequenced for bulked segregant analysis and samples collected for metabolic analysis; an isolation procedure was developed for lipid droplets from cucumber peel and metabolomic analyses have been initiated. Genetic studies in melon identified mutations in a candidate gene (APRR2), associated with light immature rind, and further indicated that this gene is also associated with color intensity of both mature rinds and flesh, making it a good target for breeding. GWAS studies utilizing the cucumber core diversity population are being performed to identify additional sources of variation for fruit surface properties, map QTL, and examine for synteny with melon. Collectively these studies identified genetic regions associated with important quality traits and contributed to our understanding of underlying biological processes associated with fruit surface development. Knowledge of genetic control of these characteristics can facilitate more efficient breeding for important fruit surface traits.