This document discusses genome sequencing and marker-based breeding in forest trees. It summarizes 3 key approaches: (1) Genome sequencing including de novo and resequencing to identify markers, (2) Marker-based breeding using genetic markers to select for traits of interest, and (3) Landscape genomics to study genetic variation across environments. It then provides more details on specific techniques used, such as quantitative trait locus mapping and association mapping to study complex traits in various tree species including loblolly pine, Douglas fir, and black cottonwood.
Genotype-By-Environment Interaction (VG X E) wth ExamplesZohaib HUSSAIN
Introduction
Phenotypic variation can be caused by the combination of genotypes and environments in a population. Genotypes are all equally sensitive to their environments, meaning that a change of environment would impact the phenotype of all genotypes to the same extent. In fact, genotypes very often have different degrees of sensitivity to environmental conditions. This cause of phenotypic variance is called genotype by- environment interaction and is symbolized by VG x E. This adds another term to the expression for the independent causes of total phenotypic variation in a population
Ve = VG + VE + VG xE
Heterotic group “is a group of related or unrelated genotypes from the same or different populations, which display similar combining ability and heterotic response when crossed with genotypes from other genetically distinct germplasm groups.”
A presentation on biometry covering issues such as the diversity of methodologies being served, its development as well as its integration with information technology.
Association mapping, also known as "linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of linkage disequilibrium to link phenotypes to genotypes.Varioius strategey involved in association mapping is discussed in this presentation
Quantitative trait loci (QTL) analysis and its applications in plant breedingPGS
Abstract
Many agriculturally important traits such as grain yield, protein content and relative disease resistance are controlled by many genes and are known as quantitative traits (also polygenic or complex traits). A quantitative trait depends on the cumulative actions of many genes and the environment. The genomic regions that contain genes associated with a quantitative trait are known as quantitative trait loci (QTLs). Thus, a QTL could be defined as a genomic region responsible for a part of the observed phenotypic variation for a quantitative trait. A QTL can be a single gene or a cluster of linked genes that affect the trait. The effects of individual QTLs may differ from each other and change from environment to environment. The genetics of a quantitative trait can often be deduced from the statistical analysis of several segregating populations. Recently, by using molecular markers, it is feasible to analyze quantitative traits and identify individual QTLs or genes controlling the traits of interest in breeding programs.
Genotype-By-Environment Interaction (VG X E) wth ExamplesZohaib HUSSAIN
Introduction
Phenotypic variation can be caused by the combination of genotypes and environments in a population. Genotypes are all equally sensitive to their environments, meaning that a change of environment would impact the phenotype of all genotypes to the same extent. In fact, genotypes very often have different degrees of sensitivity to environmental conditions. This cause of phenotypic variance is called genotype by- environment interaction and is symbolized by VG x E. This adds another term to the expression for the independent causes of total phenotypic variation in a population
Ve = VG + VE + VG xE
Heterotic group “is a group of related or unrelated genotypes from the same or different populations, which display similar combining ability and heterotic response when crossed with genotypes from other genetically distinct germplasm groups.”
A presentation on biometry covering issues such as the diversity of methodologies being served, its development as well as its integration with information technology.
Association mapping, also known as "linkage disequilibrium mapping", is a method of mapping quantitative trait loci (QTLs) that takes advantage of linkage disequilibrium to link phenotypes to genotypes.Varioius strategey involved in association mapping is discussed in this presentation
Quantitative trait loci (QTL) analysis and its applications in plant breedingPGS
Abstract
Many agriculturally important traits such as grain yield, protein content and relative disease resistance are controlled by many genes and are known as quantitative traits (also polygenic or complex traits). A quantitative trait depends on the cumulative actions of many genes and the environment. The genomic regions that contain genes associated with a quantitative trait are known as quantitative trait loci (QTLs). Thus, a QTL could be defined as a genomic region responsible for a part of the observed phenotypic variation for a quantitative trait. A QTL can be a single gene or a cluster of linked genes that affect the trait. The effects of individual QTLs may differ from each other and change from environment to environment. The genetics of a quantitative trait can often be deduced from the statistical analysis of several segregating populations. Recently, by using molecular markers, it is feasible to analyze quantitative traits and identify individual QTLs or genes controlling the traits of interest in breeding programs.
Presentation by Jacob van Etten.
CCAFS workshop titled "Using Climate Scenarios and Analogues for Designing Adaptation Strategies in Agriculture," 19-23 September in Kathmandu, Nepal.
Power Point is deals with the different aspects of Quantitative genetics in plant breeding it converse Basic Principles of Biometrical Genetics, estimation of Variability, Correlation, Principal Component Analysis, Path analysis, Different Matting design and Stability so on
The presentation was done as part of the course STAT 504 titled Quantitative Genetics in Second Semester of MSc. Agricultural Statistics at Agricultural College, Bapatla under ANGRAU, Andhra Pradesh
A presentation by Eshan Dulloo at the European Plant Genetic Resources Conference 2011. The conference brought together global particpants interested in making greater use of the agricultural biodiversity conserved in genebanks.
GGEBiplot analysis of genotype × environment interaction in Agropyron interme...Innspub Net
In order to identify genotypes of Agropyron intermedium with high forage yield and stability an experiment was carried out in the Research station of Kermanshah Iran.The 11 accessions were sown in a randomized complete block design with three replications under rainfed and irrigated conditions during 2013-21-014 cropping deasons. Combined analysis of variance indicated high significant differences for location, genotype and G × E interaction (GEI) at 1% level of probability. Mean comparisons over environments introduced G4, G3 and G5 with maximum forage yield over rainfed and irrigated conditions. Minimum forage yield was attributed to genotype G1. GGEbiplot analysis exhibited that the first two principal components (PCA) resulted from GEI and genotype effect justified 99.37% of total variance in the data set. The four environments under investigation fell into two apparent groups: irrigated and rainfed. The presence of close associations among irrigated (E1 and E3) and rainfed (E2 and E4) conditions suggests that the same information about the genotypes could be obtained from fewer test environments, and hence the potential to reduce testing cost.The which-won-where pattern of GGEbiplot introduced genotypes G3 and G4 as stable with high forage yield for rainfed condition, while G5 was stable with high yield for irrigated condition. According to the comparison of the genotypes with the Ideal genotype accessions G4, G3 and G9 were more favorable than all the other genotypes. Get more articles at: http://www.innspub.net/volume-6-number-4-april-2015-jbes/
Molecular Breeding in Plants is an introduction to the fundamental techniques...UNIVERSITI MALAYSIA SABAH
This slide describe the process of molecular breeding in plants which involves the application of molecular markers for Marker Assisted Selection and Marker Assisted Breeding.
A new era of genomics for plant science research has opened due the complete genome sequencing projects of Arabidopsis thaliana and rice. The sequence information available in public database has highlighted the need to develop genome scale reverse genetic strategies for functional analysis (Till et al., 2003). As most of the phenotypes are obscure, the forward genetics can hardly meet the demand of a high throughput and large-scale survey of gene functions. Targeting Induced Local Lesions in Genome TILLING is a general reverse genetic technique that combines chemical mutagenesis with PCR based screening to identity point mutations in regions of interest (McCallum et al., 2000). This strategy works with a mismatch-specific endonuclease to detect induced or natural DNA polymorphisms in genes of interest. A newly developed general reverse genetic strategy helps to locate an allelic series of induced point mutations in genes of interest. It allows the rapid and inexpensive detection of induced point mutations in populations of physically or chemically mutagenized individuals. To create an induced population with the use of physical/chemical mutagens is the first prerequisite for TILLING approach. Most of the plant species are compatible with this technique due to their self-fertilized nature and the seeds produced by these plants can be stored for long periods of time (Borevitz et al., 2003). The seeds are treated with mutagens and raised to harvest M1 plants, which are consequently, self-fertilized to raise the M2 population. DNA extracted from M2 plants is used in mutational screening (Colbert et al., 2001). To avoid mixing of the same mutation only one M2 plant from each M1 is used for DNA extraction (Till et al., 2007). The M3 seeds produce by selfing the M2 progeny can be well preserved for long term storage. Ethyl methane sulfonate (EMS) has been extensively used as a chemical mutagen in TILLING studies in plants to generate mutant populations, although other mutagens can be effective. EMS produces transitional mutations (G/C, A/T) by alkylating G residues which pairs with T instead of the conservative base pairing with C (Nagy et al., 2003). It is a constructive approach for users to attempt a range of chemical mutagens to assess the lethality and sterility on germinal tissue before creating large mutant populations.
Presentation by Jacob van Etten.
CCAFS workshop titled "Using Climate Scenarios and Analogues for Designing Adaptation Strategies in Agriculture," 19-23 September in Kathmandu, Nepal.
Power Point is deals with the different aspects of Quantitative genetics in plant breeding it converse Basic Principles of Biometrical Genetics, estimation of Variability, Correlation, Principal Component Analysis, Path analysis, Different Matting design and Stability so on
The presentation was done as part of the course STAT 504 titled Quantitative Genetics in Second Semester of MSc. Agricultural Statistics at Agricultural College, Bapatla under ANGRAU, Andhra Pradesh
A presentation by Eshan Dulloo at the European Plant Genetic Resources Conference 2011. The conference brought together global particpants interested in making greater use of the agricultural biodiversity conserved in genebanks.
GGEBiplot analysis of genotype × environment interaction in Agropyron interme...Innspub Net
In order to identify genotypes of Agropyron intermedium with high forage yield and stability an experiment was carried out in the Research station of Kermanshah Iran.The 11 accessions were sown in a randomized complete block design with three replications under rainfed and irrigated conditions during 2013-21-014 cropping deasons. Combined analysis of variance indicated high significant differences for location, genotype and G × E interaction (GEI) at 1% level of probability. Mean comparisons over environments introduced G4, G3 and G5 with maximum forage yield over rainfed and irrigated conditions. Minimum forage yield was attributed to genotype G1. GGEbiplot analysis exhibited that the first two principal components (PCA) resulted from GEI and genotype effect justified 99.37% of total variance in the data set. The four environments under investigation fell into two apparent groups: irrigated and rainfed. The presence of close associations among irrigated (E1 and E3) and rainfed (E2 and E4) conditions suggests that the same information about the genotypes could be obtained from fewer test environments, and hence the potential to reduce testing cost.The which-won-where pattern of GGEbiplot introduced genotypes G3 and G4 as stable with high forage yield for rainfed condition, while G5 was stable with high yield for irrigated condition. According to the comparison of the genotypes with the Ideal genotype accessions G4, G3 and G9 were more favorable than all the other genotypes. Get more articles at: http://www.innspub.net/volume-6-number-4-april-2015-jbes/
Molecular Breeding in Plants is an introduction to the fundamental techniques...UNIVERSITI MALAYSIA SABAH
This slide describe the process of molecular breeding in plants which involves the application of molecular markers for Marker Assisted Selection and Marker Assisted Breeding.
A new era of genomics for plant science research has opened due the complete genome sequencing projects of Arabidopsis thaliana and rice. The sequence information available in public database has highlighted the need to develop genome scale reverse genetic strategies for functional analysis (Till et al., 2003). As most of the phenotypes are obscure, the forward genetics can hardly meet the demand of a high throughput and large-scale survey of gene functions. Targeting Induced Local Lesions in Genome TILLING is a general reverse genetic technique that combines chemical mutagenesis with PCR based screening to identity point mutations in regions of interest (McCallum et al., 2000). This strategy works with a mismatch-specific endonuclease to detect induced or natural DNA polymorphisms in genes of interest. A newly developed general reverse genetic strategy helps to locate an allelic series of induced point mutations in genes of interest. It allows the rapid and inexpensive detection of induced point mutations in populations of physically or chemically mutagenized individuals. To create an induced population with the use of physical/chemical mutagens is the first prerequisite for TILLING approach. Most of the plant species are compatible with this technique due to their self-fertilized nature and the seeds produced by these plants can be stored for long periods of time (Borevitz et al., 2003). The seeds are treated with mutagens and raised to harvest M1 plants, which are consequently, self-fertilized to raise the M2 population. DNA extracted from M2 plants is used in mutational screening (Colbert et al., 2001). To avoid mixing of the same mutation only one M2 plant from each M1 is used for DNA extraction (Till et al., 2007). The M3 seeds produce by selfing the M2 progeny can be well preserved for long term storage. Ethyl methane sulfonate (EMS) has been extensively used as a chemical mutagen in TILLING studies in plants to generate mutant populations, although other mutagens can be effective. EMS produces transitional mutations (G/C, A/T) by alkylating G residues which pairs with T instead of the conservative base pairing with C (Nagy et al., 2003). It is a constructive approach for users to attempt a range of chemical mutagens to assess the lethality and sterility on germinal tissue before creating large mutant populations.
Tree improvement | Techniques & PracticesAnand Charvin
Tree improvement relies on understanding and using variation that naturally occurs in tree populations.
This presentation aims to allow the users to learn about tree improvement and the techniques and practices.
Protecting plant biodiversity: The ITPGRFA, genome sequencing and the relevan...FAO
The presentation includes information on the ITPGRFA's objectives, the Nagoya Protcol and its comparison with the treaty. Further information on connecting Genomics and other type of information with the Global Information System are also available in the presentation.
http://tiny.cc/FAO-COAG-GS
http;//www.fao.org
GenomeTrakr: Whole-Genome Sequencing for Food Safety and A New Way Forward in...ExternalEvents
http://www.fao.org/about/meetings/wgs-on-food-safety-management/en/
GenomeTrakr: Whole-Genome Sequencing for Food Safety and A New Way Forward in the Microbiological Testing & Traceability for Foodborne Pathogens. Presentation from the Technical Meeting on the impact of Whole Genome Sequencing (WGS) on food safety management -23-25 May 2016, Rome, Italy.
Whole genome sequencing of arabidopsis thalianaBhavya Sree
arabidopsis is the representative of plant kingdom or the 'model plant'.it is the first plant genome sequenced. the sequences lead to the overall understanding of the plant kingdom, better understanding of various genes,the important metabolic pathways, evolution etc
This presentation is explains about the genome sequencing, its traditional method and modern method. This basically focus on Next Generation Sequencing and its types.
Genomic sequencing a sub-disciplinary branch of genetics and difference between the two sequencers used to sequence the genome basically automated sequencer and fluorescence sequencers and its applications.
"Genomic approaches for dissecting fitness traits in forest tree landscapes"ExternalEvents
"Genomic approaches for dissecting fitness traits in forest
tree landscapes" presentation by Ciro De Pace, Università degli Studi della Tuscia, Viterbo, Italy
The number of sequenced genes having unknown function continues to climb with the continuing decrease in the cost of genome sequencing. In Reverse Genetics (RG), functions of known genes are investigated with targeted modulation of gene activity, and hypothesis regarding gene function directly tested in vivo. Several RG approaches like insertional mutagenesis, fast neutron mutagenesis, TILLING and RNA interference have led to the identification of mutations in candidate genes and subsequent phenotypic analysis of these mutants.
Okabe et al. (2011) employed TILLING technique to screen six ethylene receptor genes in tomato (SlETR1–SlETR6) and two allelic mutants of SlETR1 (Sletr1-1 and Sletr1-2) with reduced ethylene response were identified. Using fast neutron mutagenesis, Li et al. (2001) obtained arabidopsis deletion mutants for bZIP transcription factor viz. AHBP 1b and OBF 5, a key regulator for systemic acquired resistance but their role were compensated by other regulatory factors in mutants. Terada et al. (2007) successfully blocked the expression of the Adh 2 gene through homologous recombination followed by transgenesis in rice however phenotype could not be determined since no differences were observed between wild and transgenic plants. RNA interference (RNAi) works as sequence-specific gene regulation and has been used in determination of function of many genes. Saurabh et al. (2014) reviewed the impact of RNAi in crop improvement and found its application in improvement of nutritional aspects, biotic and abiotic stresses, morphol¬ogy, crafting male sterility, enhanced secondary metabolite synthesis.
In addition, new advances in technology and reduction in sequencing cost may soon make it practical to use whole genome sequencing or gene targeting like ZFN technology and TAL effectors technology on a routine basis to identify or generate mutations in specific genes. Scholze and Boch (2011) mentioned that TAL effectors technology is more specific and predictable than ZFN. RG techniques have their own advantages and disadvantages depending on the species being targeted and the questions being addressed. Finally, with the continuous development of new technologies, the most efficient RG technique in the future may involve high throughput direct sequencing of part or complete genomes of individual plants followed by efficient novel tools to determine the function for utilization in crop improvement.
Flow Cytometric Analysis for Ploidy and DNA Content of Banana Variants Induce...paperpublications3
Abstract: Nuclear DNA content of mutated banana plants was determined by using flow cytometric techniques. It is a powerful tool for large scale screening of ploidy levels. Nuclei were isolated from young leaves from (banana mutants & Glycine plants) supplemented with Propidium- iodide (PI) and RNAse. "Glycine max" used as internal reference standard for identifying the nuclear DNA content by FCM. For ploidy estimation DAPI was used. The results showed differences in DNA content between variants indicating the effect of gamma-irradiation on the genotype of these plants. Variants of short plant stature or stunted growth showed great differences in DNA content compared to control (non-irradiated). The phenotypic variations observed at high doses were likely due to changes in the DNA sequences at the chromosomal level. Nuclear DNA contents decreased with an increase of gamma-dose from 20 Gy to 60 Gy. However, there were no significant differences between DNA content at 20 Gy and 30 Gy and also between 40 Gy and 60 Gy, while they were differed significantly from the control. The results showed no significant differences in ploidy level between all samples used (3n); while all selected mutants (variants) showed differences in DNA content.
B4FA 2012 Tanzania: Combating cassava brown streak disease - Fortunus Anton K...b4fa
Presentation at the November 2012 dialogue workshop of the Biosciences for Farming in Africa media fellowship programme in Arusha, Tanzania.
Please see www.b4fa.org for more information
This presentation entitled 'Molecular phylogenetics and its application' deals with all the developmental ideas and basics in the field of bioinformatics.
Ponent: Francesc Piferrer (ICM - CSIC)
Abstract: La proporció de sexes és un paràmetre fonamental en la demografia de les poblacions. Es presenta el coneixement que actualment es té sobre els mecanismes moleculars que la determinen i com en molts casos hi ha una participació combinada d’elements genètics i factors ambientals. La epigenètica integra la informació genòmica amb la ambiental i és la base de la plasticitat fenotípica Es repassen breument els principals mecanismes epigenètics i diferents mètodes per a avaluar canvis en la metilació del DNA. Seguidament, es presenten exemples de com la epigenètica pot contribuir en la recerca en ecologia i, de passada, en la producció animal. Per acabar, mostrarem alguns exemples de recerca en epigenòmica en poblacions naturals de les Illes Medes, de com petites variacions en les condicions ambientals al principi de la vida tenen conseqüències a llarg termini, i discutirem breument aspectes adaptatius en un context de canvi global.
The genetic architecture of recombination rate variation in a natural populat...Susan Johnston
Genome-wide association study vs. regional heritability analysis to detect genetic variants underlying individual recombination rate variation in a wild population of Soay sheep.
Nature GeNetics VOLUME 46 NUMBER 10 OCTOBER 2014 1 0 8 9.docxgemaherd
Nature GeNetics VOLUME 46 | NUMBER 10 | OCTOBER 2014 1 0 8 9
A suite of forces and factors, including mutation, recombination,
selection, population history and gene duplication influence patterns
of intraspecific genetic variation. Distinguishing which factors have
shaped sequence variation across a genome requires extensive whole-
genome sequencing of multiple individuals, which has only recently
become tractable1. Most large-scale whole-genome resequencing
studies have focused on model and domesticated species1–5. However,
extensive sequencing of natural populations holds great promise for
advancing understanding of evolutionary biology, including identify-
ing functional variation and the molecular bases of adaptation. Recent
work in a number of species has identified genomic regions that show
signatures of positive selection, suggesting that such regions contain
loci that control adaptive traits4,6–8. Relatively few studies, however,
have combined genome-wide scans with phenotypic data to determine
whether computationally identified selected regions influence adap-
tive phenotypic variation5,9–13. Genome-wide studies of large natural
populations combined with phenotypic measurements are necessary
to determine which factors shape patterns of genetic variation within
species and, therefore, enhance understanding of adaptation.
With large geographic ranges spanning wide environmental gradi-
ents and a long history of research showing local adaptation14, forest
trees are ideal for examining the processes shaping genetic variation
in natural populations. Forest trees cover approximately 30% of ter-
restrial land area15, provide direct feedback to global climate15 and
are often foundation species that organize entire biotic communities
and biogeochemical systems16,17. Clearly, biotic and abiotic interac-
tions have influenced population sizes and distributions of forest
trees, leaving diagnostic signatures in the genomes of present-day
populations14,18,19. A deeper understanding of the evolutionary and
ecological forces that shaped these patterns will offer insights and
options for ecosystem management, applied tree improvement and
accelerated domestication efforts20.
Black cottonwood, Populus trichocarpa Torr. & Gray, is a dominant
riparian tree that has become a model for the advancement of genome-
level insights in forest trees21. The sequencing of 16 P. trichocarpa
genomes revealed widespread patterns of linkage disequilibrium (LD)
and population structure22 and extensive genecological studies have
revealed a high degree of adaptive phenotypic variation in growth,
vegetative phenology and physiological traits such as water-use effi-
ciency and photosynthesis23–25, suggesting that local adaptation is
prevalent. To date, candidate gene–association analyses have revealed
loci with significant effects on phenotypic traits26,27. However, thus
far there have been no publications describing whole-genome asso-
.
Nature GeNetics VOLUME 46 NUMBER 10 OCTOBER 2014 1 0 8 9.docxvannagoforth
Nature GeNetics VOLUME 46 | NUMBER 10 | OCTOBER 2014 1 0 8 9
A suite of forces and factors, including mutation, recombination,
selection, population history and gene duplication influence patterns
of intraspecific genetic variation. Distinguishing which factors have
shaped sequence variation across a genome requires extensive whole-
genome sequencing of multiple individuals, which has only recently
become tractable1. Most large-scale whole-genome resequencing
studies have focused on model and domesticated species1–5. However,
extensive sequencing of natural populations holds great promise for
advancing understanding of evolutionary biology, including identify-
ing functional variation and the molecular bases of adaptation. Recent
work in a number of species has identified genomic regions that show
signatures of positive selection, suggesting that such regions contain
loci that control adaptive traits4,6–8. Relatively few studies, however,
have combined genome-wide scans with phenotypic data to determine
whether computationally identified selected regions influence adap-
tive phenotypic variation5,9–13. Genome-wide studies of large natural
populations combined with phenotypic measurements are necessary
to determine which factors shape patterns of genetic variation within
species and, therefore, enhance understanding of adaptation.
With large geographic ranges spanning wide environmental gradi-
ents and a long history of research showing local adaptation14, forest
trees are ideal for examining the processes shaping genetic variation
in natural populations. Forest trees cover approximately 30% of ter-
restrial land area15, provide direct feedback to global climate15 and
are often foundation species that organize entire biotic communities
and biogeochemical systems16,17. Clearly, biotic and abiotic interac-
tions have influenced population sizes and distributions of forest
trees, leaving diagnostic signatures in the genomes of present-day
populations14,18,19. A deeper understanding of the evolutionary and
ecological forces that shaped these patterns will offer insights and
options for ecosystem management, applied tree improvement and
accelerated domestication efforts20.
Black cottonwood, Populus trichocarpa Torr. & Gray, is a dominant
riparian tree that has become a model for the advancement of genome-
level insights in forest trees21. The sequencing of 16 P. trichocarpa
genomes revealed widespread patterns of linkage disequilibrium (LD)
and population structure22 and extensive genecological studies have
revealed a high degree of adaptive phenotypic variation in growth,
vegetative phenology and physiological traits such as water-use effi-
ciency and photosynthesis23–25, suggesting that local adaptation is
prevalent. To date, candidate gene–association analyses have revealed
loci with significant effects on phenotypic traits26,27. However, thus
far there have been no publications describing whole-genome asso-
...
Forest and agroforesty options for building resilience in refugee situations:...World Agroforestry (ICRAF)
Humanitarian Networks and Partnerships Week (HNPW) 2020
Climate Crisis Inter-Network
"Fit for Purpose? Current Tools and Approaches to Mitigate Climate Risks in Humanitarian Settings"
HLPE 2019. Agroecological and other innovative approaches for sustainable agriculture and food systems that enhance food security and nutrition. A report by the High Level Panel of Experts on Food Security and Nutrition of the Committee on World Food Security, Rome
Vulnerabilities of forests and forest dependent people
Peter Minang, FTA, ICRAF
Social and environmental justice as a trigger of robust ambitious climate action and prosperous future for all
Chilean pavilion, COP 25, Madrid, 7th December 2019
An increasing multitude of insect pests and pathogens is targeting indigenous trees of natural forests, agroforestry systems, and exotic trees in planted forests in Africa. This is raising major concerns for a continent already challenged by adaptations to climate change, as it threatens a vital resource for food security of rural communities, economic growth, and ecosystem conservation. The accidental introduction through trade of non‐native species in particular is accelerating, and it adds to the damage to tree‐based landscapes by native pests and diseases. Old‐time and new invaders heavily impact planted forests of exotic eucalypts, pines, and acacias, and are spreading quickly across African regions. But many non‐native pathogens are recently found affecting important indigenous trees.
Decent work and economic growth: Potential impacts of SDG 8 on forests and fo...World Agroforestry (ICRAF)
This paper assesses the potential impact of Sustainable Development Goal (SDG) 8 on forests and forest-dependent people. The concepts of decent work and economic growth are put in the context of predominant development theories and paradigms (modernization, economic growth, basic needs, sustainable development) which shape the agendas of governments, private sector, civil society, and investors. These stakeholders pursue different goals and interests, with uneven prioritization of SDG 8 targets and mixed impacts on forests and livelihoods.
Forest conservation and socio-economic benefits through community forest conc...World Agroforestry (ICRAF)
With an extension of 2.1 million ha, the Maya Biosphere Reserve (MBR) in Petén, Guatemala is the largest protected area in Central America. To reconcile forest conservation and socio-economic development, community forest concessions were created in its Multiple Use Zone (MUZ) in the late 1990s and early 2000s. Operated by a community forest enterprise (CFE), and with a cycle of 25 years, the concessions grant usufruct rights to local communities on an area of about 400,000 ha. Currently, nine concessions are active, while the contracts of two concessions were cancelled and the management plan of another suspended.
Sustainable land management for improved livelihoods and environmental sustai...World Agroforestry (ICRAF)
A healthy viable multifunctional landscape has the capability of supporting sustainable agricultural productivity, providing agroforestry and forest products (timber, fuel wood, fruits, medicine, fertilizer, gum etc.) for the sustenance of mankind while providing other environmental services. However these products are increasingly becoming unavailable due to declining soil fertility, climatic extremes, and high costs of inputs. Identifying low-cost, sustainable ways to attain food security and sustainable environment for millions of smallholder farmers in Sub Saharan Africa (SSA) remains a major developmental challenge.
Rangelands are more than just grass but rather complex and biodiverse ecosystems. Covering nearly half the world’s land area, they are in need of restoration and sustainable management.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
10. a b c a b c a b c a b c A B C A B C A B C A B C X X Parent 3 Parent 4 Parent 1 Parent 2 A B C a b c F1 A B c a B C a B C A B c A b c a b C a b C A b c A b c a B C ABc a b C a B c A b c A b c A b c a B C a B c Bb Bb Bb BB BB BB bb bb bb HEIGHT BB Bb bb GENOTYPE Quantitative Trait Locus Mapping A B C a b c X F1 B b Knott et al. (1997) TAG 84:810-820
16. 2 r2 2n 1n Association Genetics in Conifers Large and Random Mating Population Neale & Savolainen. 2004. Trends in Plant Science. 9:325-330
17. Three approaches to MAS(classified by mapping precision) Modified from Grattapaglia (2007)
18. DNA microarrays to identify genes implicated in the formation of the wood cell wall, through studies of their specific regulation, abundance, or interactions 2000-2003 Expressed genes identification from differentiating xylem (71,377 ESTs in Genbank) QTL mapping Association mapping
19. Phenotype Wood Properties 2001-2004 Water Deficit Resequence SNP Disease Resistance Association Genotype: Illumina- BeadStation 500G-BeadLab Platform, 150,000 data points per week at UCD Genome Center
22. High throughput SNP genotyping in forest trees Pre-SNP era, average marker data points per study ~ 5,000 data points Assume 2,000 studies in total X 5,000 data points ~ 10M data points Last 5 years, forest tree projects at UCD-GC ~ 33M data points
23. wood specific gravity Wood Quality traits microfibril angle S3 secondary wall S2 S1 primary wall cell wall chemistry early late lignin hemicellulose cellulose
26. Water Use Efficiency Stable carbon isotope discrimination in foliage, in two sites (Cuthbert & Palatka). Strong family structure (partial diallel), including 15-24 offspring from 61 families. Cuthbert Palatka
27. FBRC association population in loblolly pine Partial diallel, 15-24 offspring from 61 families. Association with CID (Carbon Isotope Discrimination, related to Water Use Efficiency, in two sites: Cuthbert and Palatka). Analyses using the Quantitative Transmission Disequilibrium Test (QTDT) González-Martínezet al. 2008. Heredity. 101:19-26
37. PineSAP – Sequence Alignment and SNP Identification DNASam – DNA Sequence Analysis and Manipulation Wegrzyn et al. 2009 Bioinformatics 25:2609-2610 Eckert et al 2010 Molecular Ecology Resources 10:542-545 http://dendrome.ucdavis.edu
43. Disease resistanceAssociation Population (409 clones) SNP markers Illumina Infinium: 3938 SNPs for 3100 genes Eckert et al. 2010. Genetics 185: 969-982. Eckert et al. 2010. Genetics 185: 969-982.
44. We couldn’t afford one of those cool PCR robots, so we just got 2 graduate students and a cardboard box. The Cartoon Lab by Ed Himelblau 1055 384-well plates!
45. ADEPT2: Gene Expression Phenotypes: Main Results: 81 SNPs (FDR Q < 0.10) associated to expression for 33 xylogenesis genes: 31 SNPs were nonsynonymous 18 SNPs were synonymous 20 SNPs were intronic 12 SNPs were in UTRs Effect sizes for SNPs in range 1.5-4.5% (r2 from GLM) Most effects were non-additive and due to rare alleles Pleiotropy inferred for 8 genes ΔΔCT values from 112 xylogenesis related genes Palleet al. (2011) Tree Genetics and Genomes. 7:193-206.
46. ADEPT2: Metabolome Phenotypes: Main Results: 61 associations (FDR Q < 0.10) involving 56 SNPs and 44 metabolites. Effect sizes moderate for single SNPs (r2: 4-12%) 292 metabolites from GC-TOF-MS including free amino acids, free fatty acids, sugars and a number of organic acids Statistical Models: Regression on ancestry corrected genotypes and phenotypes for each SNP Bayesian linear mixed models with multiple SNPs and terms for kinship and population structure Eckert et al. New Phytologist (Submitted)
47. ADEPT2: Drought-Tolerance Phenotypes: Main Results: Broad sense heritability 0.4-0.5 Moderate genetic correlations among phenotypes (0.3-0.4). 14 associations detected (FDR Q < 0.05): 6 SNPs with foliar nitrogen 7 SNPs with d13C 1 SNP with height SNP effects small to moderate (GLM: r2 4-9%) Effects largely additive Associated SNPs were mostly to SNPs with low minor allele frequencies (MAF < 0.10). Carbon isotope ratio (d13C), foliar nitrogen content and 2nd year height measured in common garden. BLUPs incorporated spatially autocorrelated errors across the common garden. Statistical Models: Linear mixed and general linear models with and without population structure and kinship corrections for each SNP and trait Cumbieet al. (2011) Heredity Online.
48. ADEPT2: Disease-Resistance Phenotypes: Main Results: 10 associations with small effects for a diverse set of genes Lesion length post infection with Fusarium circinatum collected after 4, 8, and 12 weeks Statistical Models: Bayesian linear mixed models with multiple SNPs and terms for kinship and population structure Quesada et al.(2010) Genetics 186:677-686
51. 7 are of unknown function, predicted proteins, or have no sequence similarity with genes in the databasePeter et al. (unpublished)
52. ADEPT2: Environmental Associations Environmental Gradients: Main Results: 5 associations (FDR Q < 0.10) with small effects mostly with aridity during spring. Eckert et al. 2010. Genetics 185: 969-982. Seasonal aridity gradients across the range of loblolly pine. Statistical Models: Regression on ancestry corrected genotypes and phenotypes for each SNP Ancestry corrections performed via multiple regression and PCA. Eckert et al. 2010. Genetics 185: 969-982.
60. Tree Improvement Infrastructure Tree Improvement Cooperatives: Long-term collaborations with public, private, & academic partners Distributed ownership & responsibilities Goal: to support regeneration activities and decision tools
78. Tree breeders must be trained in the application of genomic breeding technologies
79.
80. Guiding Principles of the Loblolly Pine Genome Project EMPOWERMENT. Our goal is to develop the technologies, platforms and bioinformatics infrastructures to rapidly and inexpensively sequence large and complex genomes of coniferous forest trees. This will allow the forestry community to begin sequencing the many genomes of economic and ecological importance without a dependence on centralized genome centers. ADAPTIVE. We recognize the sequencing technologies are developing rapidly and that we must have the expertise and flexibility to rapidly adopt new approaches into our overall sequencing strategy. COMPARATIVE. We recognize the power of comparative genomics approaches in assembling and annotating genome sequences and will use this approach throughout the project.
81. The pine genome is characterized by diverse and highly diverged sequences Anna S. Kovach1, Jill L. Wegrzyn2, Genis Parra3, Carson Holt4, George E. Bruening5, Carol Loopstra6, James Hartigan7, Mark Yandell4, Charles H. Langley8, Ian Korf3, David B. Neale2,9 1 Genetics Graduate Group, University of California, Davis, CA 95616, USA. 2 Department of Plant Sciences, University of California, One Shields Avenue, Davis, CA 95616, USA. 3 Genome Center, Division of Biological Sciences, University of California, Davis, CA 95616, USA. 4Eccles Institute of Human Genetics, University of Utah, Salt Lake City, Utah 84112, USA. 5 Department of Plant Pathology, University of California, Davis, CA 95616, USA. 6Dept of Ecological Science and Management, Texas A&M University, College Station, TX 77843, USA. 7Agencourt Bioscience Corporation, Beverly, MA 01915, USA. 8 Section of Evolution and Ecology, University of California at Davis, Davis, CA 95616, USA. 9 Institute of Forest Genetics, USDA Forest Service, Davis, CA 95616, USA. Kovach A.S., Wegrzyn J.L., Parra G., Holt C., Bruening G.E., Loopstra C.A., Hartigan J., Yandell M., Langley C.H., Korf I., Neale D.B. (2010) The Pinustaeda genome is characterized by diverse and highly diverged repetitive sequences. BMC Genomics. 11:1-38.
82. Kovach A.S., Wegrzyn J.L., Parra G., Holt C., Bruening G.E., Loopstra C.A., Hartigan J., Yandell M., Langley C.H., Korf I., Neale D.B. (2010) The Pinustaeda genome is characterized by diverse and highly diverged repetitive sequences. BMC Genomics. 11:1-38.
83.
84. Conifer Comparative Genomics Project ( http://dendrome.ucdavis.edu/ccgp ) loblolly pine/Douglas Fir loblolly pine/slash pine loblolly pine/sugar pine
85. “I like trees because they seem more resigned to the way they have to live than other things do” ~ Willa Cather 1913
86. ADAPTATION IN ALPINE CONIFERS David B Neale – UC Davis Elena Mosca, Erica Di Pierro, Nicola La Porta – FEM Giovanni Vendramin – CNR Firenze Piero Belletti – Torino University
87. Introduction Coniferous forests are potentially quite sensitive to climate change Climate change effects: - shift in species ranges to higher elevations due to increase in T Fagus sylvatica L. Pinus mugo - change in forest stand species richness - effects on the interactions among species within the same habitat Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
88. Picea abies Species studied Larix decidua Abiesalba Pinus mugo Aim -effects of climate on conifer population genetics - evidence of local adaptation along environmental gradient Pinus cembra Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
89. CONIFEROUS FORESTS CLIMATE CHANGE EXTINCTION persistence through MIGRATION persistence through ADAPTATION GENETIC DIVERSITY CONSERVATION Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
90. 1. GENETIC DIVERSITY Definition: measure the degree of polymorphism within a population SNP = Single Nucleotide Polymorphism Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
91. Re-sequencing project: Aim: studying the genetic diversity in forest populations Larix decidua Abiesalba Pinus mugo Pinus cembra Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
92. Results: Estimates of genetic diversity: - Watterson’s θ and θπ Genetic diversity: - count of SNP number P. cembra has low genetic diversity Highly adapted In danger ?! Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
93. 2. ADAPTATION Aim: studying the possible interactions between genetic data and environmental factors Methods: ENVIRONMENT DATA SAMPLING PINE NEEDLES GPS DEVICE MODIS/ECA&D TOOLS GENOTYPING CHIP GPS location, Temperature Precipitation… Single Nucleotide Polymorphism DATA ANALYSIS Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
94. 1.Sampling a. Macroscale level: geographical distribution Environmental factors: Elevation Soil Type Expositions Pure/Mixed stands Picea abies/Abies alba Pinus mugo/Pinus cembra Ecological extremes Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
95. A. alba P. abies P. mugo L. decidua P. cembra b. Local scale: Trentino-Alto Adige Provinces - Altitudinal gradient: 2 aspects: North/South 3 plots: high/medium/low elevation 25 trees per plot - Soil gradient: 2 types: lime /silicate soil 2 sides: West/East Adige 65 trees per site -Ecological extremes 25 trees per site - Pure/Mixed stands Picea abies/Abies alba Pinus mugo/Pinus cembra Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
96. On the field - fresh needles collection for each tree In the lab - make the fresh needles dry - DNA extraction Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
97. 2. SNP Genotyping: definition - is the measurement of genetic variations of SNP between species members. Chip Distribution of reaction AA AB BB Fluorescence Data visualization Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
98. 2. Genotyping chip: design SNPs selection : Genotyping chip design: Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
99. AA AB BB Good 3. Data quality checking and final dataset production Bad Finaldataset Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
100. BZ TN 4a. Population structure analysis: STRUCTURE Pritchard et al. Genetics 2000 Picea abies K=4 DISCRIMINANT ANALYSIS of PRINCIPAL COMPONENTS Jombart et al. BMC Genetics 2010 K=3 Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
101. K=3 Abies alba K=7 K=8 Larix decidua K=3 Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
102. K=4 Pinus cembra K=6 K=4 K=4 Pinus mugo Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
103. 4b. Genetic data and geography: A. alba L. decidua 3 2 1 5 4 PCA between geographic areas P. cembra P. mugo Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
104. 4c. Genetic data and climatic data: Multivariate analysis 3 2 A. alba L. decidua 1 4 PCA on these factors: -Lat & Long -Elevation -Aspect -Slope -seasonal T average -seasonal T max and T min -seasonal cumulate P P. cembra P. mugo Impatto dei cambiamenti climatici sulla biodiversita' in Trentino
105. Bayesian analysis Bayenv Coop et al. Genetics 2010 N of SNPs with BF factor > 3 3 2 1 4 MAF and PC2 score A. alba PC2 seasonal T min, T min coldest month, T mean driest quarter
The plot in the lower left gives the sampled counties and population structure estimates for the NCSU population. Colors designate different genetic clusters. The plot on the right is a generic SNP genotyping plot used to call SNP genotypes.
The graph shows the inferred gene network for the targeted genes from Sree’s TGG paper.
The colored matrix gives all pairwise correlations among 292 metabolites. The histogram shows the distribution of the values colored in part A. The plot in the lower right lists in order (top to bottom) of the % phenotypic variance explained for SNPs identified in the Bayesian linear mixed models in a general linear model with population structure covariates. These are the bars. The line gives the # of SNPs identified in the Bayesian linear mixed models with significant effects.
Photo is of the NCSU common garden. The plot shows the spatial variogram across the garden.
Shown in the plot is the distribution of lesion length BLUPs from Quesada et al. 2010. Effect in the table gives the SNP effect/phenotypic standard deviation as a percent. This then gives the effect size scaled to the variation in the phenotype.