FIsherOrr_maize
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This document discusses the evolution of corn from its ancestral plant teosinte and how it has changed phenotypically over time through selection. It references the Fisher-Orr model and a 1998 paper by Orr on evolution to provide context on corn's movement through phenotypic space from teosinte to modern landraces and corn.
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Yellow corn
The document discusses corn production in the Philippines. It notes that corn yields are low on average compared to other major corn producing countries. While yellow corn areas have seen higher yields due to new varieties, white corn yields have grown slowly. Low adoption of technologies, high losses, and transportation and marketing costs have kept domestic corn production costs above import prices. As a result, corn areas and production have declined in recent decades. The corn sector now faces further challenges from trade liberalization commitments. The goal of the Ginintuang Masaganang Ani for Corn program is to increase productivity and incomes through improved technologies, marketing, and partnerships between government and the private sector.
Drift
The document discusses the concept of genetic drift, which is the change in allele frequencies over time due to random chance rather than natural selection. It provides examples of genetic drift occurring through bottlenecks, founder effects, and stochastic sampling in populations that have experienced reductions in size. The document then simulates genetic drift through a "Haploid Sex with Chocolate" activity, where students exchange M&M "gametes" over multiple generations to model how drift can change allele frequencies randomly over time in a finite population.
maize
- Maize originated in Mexico from a wild grass called teosinte. Teosinte is considered the wild progenitor of maize because it has the same chromosome number and similar genetic constitution.
- Maize evolved from a direct domestication of an annual Mexican teosinte around 6000-10,000 years ago. Early maize had many differences from modern maize in appearance but was genetically similar.
- Cytogenetic evidence also supports maize's evolution from teosinte. Teosinte and maize have the same chromosome number, can hybridize and produce fertile offspring, while other grasses like tripsacum have different chromosome numbers and are more distantly related.
A bad genetic history of maize
Deleterious alleles have played an important role in the evolution of maize and teosinte. Although they vary in their strength and effect across populations or environments, such mutations have played a role in local adaptation in teosinte, the accumulation of load during domestication and dispersal of maize, local adaptation of maize landraces, and ultimately in hybrid vigor for agronomic traits in breeding programs.
Adaptation in plant genomes: bigger is different
Here we have proposed the functional space hypothesis, positing that mutational target size scales with genome size, impacting the number, source, and genomic location of beneficial mutations that contribute to adaptation. Though motivated by preliminary evidence, mostly from Arabidopsis and maize, more data are needed before any rigorous assessment of the hypothesis can be made. If correct, the functional space hypothesis suggests that we should expect plants with large genomes to exhibit more functional mutations outside of genes, more regulatory variation, and likely less signal of strong selective sweeps reducing diversity. These differences have implications for how we study the evolution and development of plant genomes, from where we should look for signals of adaptation to what patterns we expect adaptation to leave in genetic diversity or gene expression data. While flowering plant genomes vary across more than three orders of magnitude in size, most studies of both functional and evolutionary genomics have focused on species at the extreme small edge of this scale. Our hypothesis predicts that methods and results from these small genomes may not replicate well as we begin to explore large plant genomes. Finally, while we have focused here on evidence from plant genomes, we see no a priori reason why similar arguments might not hold in other taxa as well.
Parallel Altitudinal Clines Reveal Adaptive Evolution Of Genome Size In Zea mays
While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.
Genome size and adaptation in plants
Intraspecific adaptive variation in genome size in maize. The effects of genome size on adaptation across species.
Recommended
Yellow corn
The document discusses corn production in the Philippines. It notes that corn yields are low on average compared to other major corn producing countries. While yellow corn areas have seen higher yields due to new varieties, white corn yields have grown slowly. Low adoption of technologies, high losses, and transportation and marketing costs have kept domestic corn production costs above import prices. As a result, corn areas and production have declined in recent decades. The corn sector now faces further challenges from trade liberalization commitments. The goal of the Ginintuang Masaganang Ani for Corn program is to increase productivity and incomes through improved technologies, marketing, and partnerships between government and the private sector.
Drift
The document discusses the concept of genetic drift, which is the change in allele frequencies over time due to random chance rather than natural selection. It provides examples of genetic drift occurring through bottlenecks, founder effects, and stochastic sampling in populations that have experienced reductions in size. The document then simulates genetic drift through a "Haploid Sex with Chocolate" activity, where students exchange M&M "gametes" over multiple generations to model how drift can change allele frequencies randomly over time in a finite population.
maize
- Maize originated in Mexico from a wild grass called teosinte. Teosinte is considered the wild progenitor of maize because it has the same chromosome number and similar genetic constitution.
- Maize evolved from a direct domestication of an annual Mexican teosinte around 6000-10,000 years ago. Early maize had many differences from modern maize in appearance but was genetically similar.
- Cytogenetic evidence also supports maize's evolution from teosinte. Teosinte and maize have the same chromosome number, can hybridize and produce fertile offspring, while other grasses like tripsacum have different chromosome numbers and are more distantly related.
A bad genetic history of maize
Deleterious alleles have played an important role in the evolution of maize and teosinte. Although they vary in their strength and effect across populations or environments, such mutations have played a role in local adaptation in teosinte, the accumulation of load during domestication and dispersal of maize, local adaptation of maize landraces, and ultimately in hybrid vigor for agronomic traits in breeding programs.
Adaptation in plant genomes: bigger is different
Here we have proposed the functional space hypothesis, positing that mutational target size scales with genome size, impacting the number, source, and genomic location of beneficial mutations that contribute to adaptation. Though motivated by preliminary evidence, mostly from Arabidopsis and maize, more data are needed before any rigorous assessment of the hypothesis can be made. If correct, the functional space hypothesis suggests that we should expect plants with large genomes to exhibit more functional mutations outside of genes, more regulatory variation, and likely less signal of strong selective sweeps reducing diversity. These differences have implications for how we study the evolution and development of plant genomes, from where we should look for signals of adaptation to what patterns we expect adaptation to leave in genetic diversity or gene expression data. While flowering plant genomes vary across more than three orders of magnitude in size, most studies of both functional and evolutionary genomics have focused on species at the extreme small edge of this scale. Our hypothesis predicts that methods and results from these small genomes may not replicate well as we begin to explore large plant genomes. Finally, while we have focused here on evidence from plant genomes, we see no a priori reason why similar arguments might not hold in other taxa as well.
Parallel Altitudinal Clines Reveal Adaptive Evolution Of Genome Size In Zea mays
While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.
Genome size and adaptation in plants
Intraspecific adaptive variation in genome size in maize. The effects of genome size on adaptation across species.
Adaptive evolution of genome size across altitudinal clines in maize
Genome size in plants can vary by orders of magnitude, but this variation has long been considered to be of little to no functional consequence.
Studying three independent adaptations to high elevation in Zea mays, we find that genome size experiences parallel pressure from natural selection, causing a linear reduction in genome size with increasing altitude.
Though reductions in repetitive content are responsible for the genome size change, we find that repeats are not targeted uniformly, but that the same repetitive sequences are removed as Z. mays taxa move to higher altitude.
To identify the phenotype influenced by genome size, we study how 20% variation in genome size in a single teosinte population impacts leaf growth.
We find that genome size variation correlates negatively with cell production rate but not cell size, suggesting that individuals with larger genomes require longer to complete a mitotic cycle.
We reanalyze data from maize inbreds to show that slower cell production can lead to a delay in flowering time, suggesting that genome size can be used as a developmental clock to help adapt maize to different altitudes.
Gene flow and cross-incompatibility in maize and teosinte
This document discusses adaptive and non-adaptive introgression between maize and its wild ancestor teosinte. It describes how strong sexual selection can reduce genetic differentiation between populations by increasing mating opportunities for rare males. A two-locus population genetic model is used to show how trait and preference frequencies in two diverged populations decrease with stronger sexual selection after contact is reestablished through migration. The document also reviews evidence of maize domestication from archaeological sites in Mexico and genetic studies tracing the flow of alleles from teosinte into maize and vice versa.
Evolutionary genetics of hybrid maize
The document discusses how breeding has impacted genetic diversity in maize genomes over time. It examines changes in ancestry across the maize genome and how the genome has responded to selection for increasing hybrid yield. Specifically, it finds that changing ancestry, not selection sweeps, has driven diversity loss across heterotic groups. The diversity of ancestral lines making up modern inbreds has decreased as germplasm pools have become smaller and more homogeneous. Within a single breeding program, genetic drift in small breeding populations also reduced diversity despite selection for yield.
Evolutionary Genetics of Complex Genome
This document discusses the genetic adaptations that occurred during the domestication of maize from its wild ancestor, teosinte. It provides examples of genes that showed changes in regulatory sequences or expression levels during domestication, allowing traits like ear size and plant architecture to evolve. Genomic studies have found that a large portion of selective sweeps during maize domestication occurred in intergenic regulatory regions, suggesting selection acted upon standing genetic variation to change gene expression. Maize was domesticated independently in Mexico and South America, with genetic differences accumulating between the two gene pools over time.
JGI: Genome size impacts on plant adaptation
Genome size may impact how plant genomes adapt, offering larger mutational targets leading to more adaptation from standing variation and more adaptation in noncoding regions.
Demography and deleterious alleles in maize
1) Maize experienced a population bottleneck during domestication from its wild ancestor, teosinte, followed by a massive population expansion as maize spread across the Americas.
2) Both the long-term and recent demographic changes in maize have affected the patterns and impacts of purifying selection against deleterious alleles.
3) Simulations show that a population bottleneck reduces neutral diversity and the effects of purifying selection on linked sites, while a large population expansion can overcome the effects of purifying selection on linked sites.
Langebio 2015
The document summarizes research on the selection and demography of maize evolution. It discusses how maize was domesticated from its wild ancestor, teosinte, through selection on specific genes like tga1 and tb1 that contributed to changes in plant architecture. It also describes the spread of maize from its center of domestication in Mexico to other regions, noting evidence of selection during this spread. Genomic analyses reveal thousands of genes underwent changes between teosinte and modern maize varieties through both hard sweeps on individual genes and polygenic adaptation.
2015 SF Exploratorium Lecture: "Corn: Diversity and Origins"
Public lecture at the San Francisco Exploratorium on corn. Part of their Science of Food series http://www.exploratorium.edu/press-office/press-releases/science-food-series-launches-exploratorium
Toronto 2015
This document summarizes research on the selection and demography of maize evolution. It discusses how maize was domesticated from its wild ancestor, teosinte, through selection for traits like ear size. The document presents several genetic studies that analyzed differences between maize and teosinte genomes and identified genes underlying key domestication traits. It also describes the spread of maize from its origin center in Mexico to other regions in Mexico and South America and genetic differences between lowland and highland maize varieties.
Danforth 2015
This document summarizes research on adaptation in maize during and after domestication. It discusses how maize adapted through standing genetic variation, regulatory changes, and polygenic adaptation using multiple mutations and alleles from teosinte. It describes the origins and spread of maize from its ancestor teosinte in Mexico around 9,000 years ago to other regions of Mexico, South America, and beyond. The differences between lowland and highland maize populations are also summarized.
Presentation at SMBEBA
1) The document discusses the demography and evolution of maize and its wild ancestor teosinte. It presents genetic evidence showing that maize underwent a population bottleneck during domestication but has since expanded to a very large population size due to modern agricultural practices.
2) Studies analyzing DNA polymorphism in maize and teosinte have found that maize has significantly lower genetic diversity than teosinte, consistent with a domestication bottleneck. However, the diversity in maize is higher than expected based on its current population size due to ancient large population sizes prior to modern agriculture.
3) Models of the long-term effective population sizes of maize and teosinte show that while maize experienced a severe
Complex adaptation in Zea
- The document discusses research on the evolution and adaptation of maize and its wild relatives like teosinte. It summarizes several studies that mapped genes controlling traits like prolificacy (branching) that were selected during domestication, finding selection at the gene gt1.
- Studies find evidence of both hard and partial sweeps during selection for traits like increased branching, with convergent evolution occurring through both multiple mutations and standing variation at gt1.
- Research also examines the adaptation of maize as it spread from Mexico to the highlands and South America, finding evidence of introgression between wild and domesticated populations that aided this adaptation.
Introgression and the origin of maize in Mexico and the Southwest US
This document summarizes research on the origins and domestication of maize. It finds that maize originated from teosinte in Mexico and that ancestral reconstruction methods are needed to resolve origins due to gene flow between wild and domesticated populations. Introgression from an extinct wild grass adapted maize to high altitude environments in Mexico. Ancient DNA evidence shows that maize arrived in the Southwest US via the highlands of Mexico with subsequent gene flow from the Pacific coast. Key domestication genes like teosinte branched1 were under selection during maize's spread and adaptation.
Population genetics of maize domestication, adaptation, and improvement
The domestication of maize ~10,000 years ago resulted in dramatic differentiation from its wild ancestor teosinte. Subsequently, maize spread rapidly across the Americas, adapting to a number of new environments. Beginning in the 20th century, maize has also been subjected to intensive artificial selection by breeders. Each of these periods of adaptation have left their mark on patterns of genetic diversity. I will discuss some of our recent work using population genetics to learn about the history and process of adaptation in maize.
Bottlenecks -- some ramblings and a bit of data from maize PAGXXII
1) The document discusses how population bottlenecks during domestication can reduce genetic diversity and influence patterns of variation across the genome.
2) Bottlenecks are shown to increase the number of rare variants, affect site frequency spectra, and influence the effects of purifying selection. They can also mimic signals of positive selection.
3) Studies of maize domestication estimate a weaker bottleneck than previously thought, with rapid recent population growth increasing diversity from resequencing data. However, selection still reduces diversity more in genic regions relative to intergenic regions.
Deleterious Alleles in maize, talk from PAGXXII
This document discusses deleterious alleles in maize and their implications. It finds that:
1) Maize accumulates around 90 new mutations per meiosis, most of which are deleterious. Studies have found many new mutations of large effect in maize.
2) Genes show signatures of purifying selection, with deleterious variants found at lower frequencies compared to non-genic regions. These deleterious variants likely contribute to inbreeding depression.
3) Analysis of a panel of 282 maize inbreds found that genes containing deleterious alleles were enriched in genome-wide association studies hits for traits related to heterosis.
4) The patterns observed are consistent with a model of complementation playing
Ecogen2013
1) The document describes research on adaptation to high altitudes in maize (Zea mays).
2) It finds evidence of high altitude adaptation in wild teosinte populations in Mexico, as well as parallel adaptation in domesticated highland maize varieties through genetic changes including inversions.
3) The research identifies candidate genes and loci underlying high altitude adaptation through genome-wide association studies and comparisons to teosinte, finding evidence of past adaptive introgression from teosinte into highland maize populations.
Historical Genomics of US Maize: Domestication and Modern Breeding
This document summarizes research on the historical genomics of maize evolution in North America. The study applied population genetic analysis to genome sequencing data from maize and teosinte lines to analyze patterns of evolution during domestication and modern breeding. They found distinct impacts of selection during these two epochs and identified candidate genes targeted during each. A separate analysis of a panel of 400 North American corn belt lines genotyped over time found decreasing genetic diversity and ancestral contributions, indicating selection shaped the genetic structure of modern maize.
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Adaptive evolution of genome size across altitudinal clines in maize
Genome size in plants can vary by orders of magnitude, but this variation has long been considered to be of little to no functional consequence.
Studying three independent adaptations to high elevation in Zea mays, we find that genome size experiences parallel pressure from natural selection, causing a linear reduction in genome size with increasing altitude.
Though reductions in repetitive content are responsible for the genome size change, we find that repeats are not targeted uniformly, but that the same repetitive sequences are removed as Z. mays taxa move to higher altitude.
To identify the phenotype influenced by genome size, we study how 20% variation in genome size in a single teosinte population impacts leaf growth.
We find that genome size variation correlates negatively with cell production rate but not cell size, suggesting that individuals with larger genomes require longer to complete a mitotic cycle.
We reanalyze data from maize inbreds to show that slower cell production can lead to a delay in flowering time, suggesting that genome size can be used as a developmental clock to help adapt maize to different altitudes.
Gene flow and cross-incompatibility in maize and teosinte
This document discusses adaptive and non-adaptive introgression between maize and its wild ancestor teosinte. It describes how strong sexual selection can reduce genetic differentiation between populations by increasing mating opportunities for rare males. A two-locus population genetic model is used to show how trait and preference frequencies in two diverged populations decrease with stronger sexual selection after contact is reestablished through migration. The document also reviews evidence of maize domestication from archaeological sites in Mexico and genetic studies tracing the flow of alleles from teosinte into maize and vice versa.
Evolutionary genetics of hybrid maize
The document discusses how breeding has impacted genetic diversity in maize genomes over time. It examines changes in ancestry across the maize genome and how the genome has responded to selection for increasing hybrid yield. Specifically, it finds that changing ancestry, not selection sweeps, has driven diversity loss across heterotic groups. The diversity of ancestral lines making up modern inbreds has decreased as germplasm pools have become smaller and more homogeneous. Within a single breeding program, genetic drift in small breeding populations also reduced diversity despite selection for yield.
Evolutionary Genetics of Complex Genome
This document discusses the genetic adaptations that occurred during the domestication of maize from its wild ancestor, teosinte. It provides examples of genes that showed changes in regulatory sequences or expression levels during domestication, allowing traits like ear size and plant architecture to evolve. Genomic studies have found that a large portion of selective sweeps during maize domestication occurred in intergenic regulatory regions, suggesting selection acted upon standing genetic variation to change gene expression. Maize was domesticated independently in Mexico and South America, with genetic differences accumulating between the two gene pools over time.
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Demography and deleterious alleles in maize
1) Maize experienced a population bottleneck during domestication from its wild ancestor, teosinte, followed by a massive population expansion as maize spread across the Americas.
2) Both the long-term and recent demographic changes in maize have affected the patterns and impacts of purifying selection against deleterious alleles.
3) Simulations show that a population bottleneck reduces neutral diversity and the effects of purifying selection on linked sites, while a large population expansion can overcome the effects of purifying selection on linked sites.
Langebio 2015
The document summarizes research on the selection and demography of maize evolution. It discusses how maize was domesticated from its wild ancestor, teosinte, through selection on specific genes like tga1 and tb1 that contributed to changes in plant architecture. It also describes the spread of maize from its center of domestication in Mexico to other regions, noting evidence of selection during this spread. Genomic analyses reveal thousands of genes underwent changes between teosinte and modern maize varieties through both hard sweeps on individual genes and polygenic adaptation.
2015 SF Exploratorium Lecture: "Corn: Diversity and Origins"
Public lecture at the San Francisco Exploratorium on corn. Part of their Science of Food series http://www.exploratorium.edu/press-office/press-releases/science-food-series-launches-exploratorium
Toronto 2015
This document summarizes research on the selection and demography of maize evolution. It discusses how maize was domesticated from its wild ancestor, teosinte, through selection for traits like ear size. The document presents several genetic studies that analyzed differences between maize and teosinte genomes and identified genes underlying key domestication traits. It also describes the spread of maize from its origin center in Mexico to other regions in Mexico and South America and genetic differences between lowland and highland maize varieties.
Danforth 2015
This document summarizes research on adaptation in maize during and after domestication. It discusses how maize adapted through standing genetic variation, regulatory changes, and polygenic adaptation using multiple mutations and alleles from teosinte. It describes the origins and spread of maize from its ancestor teosinte in Mexico around 9,000 years ago to other regions of Mexico, South America, and beyond. The differences between lowland and highland maize populations are also summarized.
Presentation at SMBEBA
1) The document discusses the demography and evolution of maize and its wild ancestor teosinte. It presents genetic evidence showing that maize underwent a population bottleneck during domestication but has since expanded to a very large population size due to modern agricultural practices.
2) Studies analyzing DNA polymorphism in maize and teosinte have found that maize has significantly lower genetic diversity than teosinte, consistent with a domestication bottleneck. However, the diversity in maize is higher than expected based on its current population size due to ancient large population sizes prior to modern agriculture.
3) Models of the long-term effective population sizes of maize and teosinte show that while maize experienced a severe
Complex adaptation in Zea
- The document discusses research on the evolution and adaptation of maize and its wild relatives like teosinte. It summarizes several studies that mapped genes controlling traits like prolificacy (branching) that were selected during domestication, finding selection at the gene gt1.
- Studies find evidence of both hard and partial sweeps during selection for traits like increased branching, with convergent evolution occurring through both multiple mutations and standing variation at gt1.
- Research also examines the adaptation of maize as it spread from Mexico to the highlands and South America, finding evidence of introgression between wild and domesticated populations that aided this adaptation.
Introgression and the origin of maize in Mexico and the Southwest US
This document summarizes research on the origins and domestication of maize. It finds that maize originated from teosinte in Mexico and that ancestral reconstruction methods are needed to resolve origins due to gene flow between wild and domesticated populations. Introgression from an extinct wild grass adapted maize to high altitude environments in Mexico. Ancient DNA evidence shows that maize arrived in the Southwest US via the highlands of Mexico with subsequent gene flow from the Pacific coast. Key domestication genes like teosinte branched1 were under selection during maize's spread and adaptation.
Population genetics of maize domestication, adaptation, and improvement
The domestication of maize ~10,000 years ago resulted in dramatic differentiation from its wild ancestor teosinte. Subsequently, maize spread rapidly across the Americas, adapting to a number of new environments. Beginning in the 20th century, maize has also been subjected to intensive artificial selection by breeders. Each of these periods of adaptation have left their mark on patterns of genetic diversity. I will discuss some of our recent work using population genetics to learn about the history and process of adaptation in maize.
Bottlenecks -- some ramblings and a bit of data from maize PAGXXII
1) The document discusses how population bottlenecks during domestication can reduce genetic diversity and influence patterns of variation across the genome.
2) Bottlenecks are shown to increase the number of rare variants, affect site frequency spectra, and influence the effects of purifying selection. They can also mimic signals of positive selection.
3) Studies of maize domestication estimate a weaker bottleneck than previously thought, with rapid recent population growth increasing diversity from resequencing data. However, selection still reduces diversity more in genic regions relative to intergenic regions.
Deleterious Alleles in maize, talk from PAGXXII
This document discusses deleterious alleles in maize and their implications. It finds that:
1) Maize accumulates around 90 new mutations per meiosis, most of which are deleterious. Studies have found many new mutations of large effect in maize.
2) Genes show signatures of purifying selection, with deleterious variants found at lower frequencies compared to non-genic regions. These deleterious variants likely contribute to inbreeding depression.
3) Analysis of a panel of 282 maize inbreds found that genes containing deleterious alleles were enriched in genome-wide association studies hits for traits related to heterosis.
4) The patterns observed are consistent with a model of complementation playing
Ecogen2013
1) The document describes research on adaptation to high altitudes in maize (Zea mays).
2) It finds evidence of high altitude adaptation in wild teosinte populations in Mexico, as well as parallel adaptation in domesticated highland maize varieties through genetic changes including inversions.
3) The research identifies candidate genes and loci underlying high altitude adaptation through genome-wide association studies and comparisons to teosinte, finding evidence of past adaptive introgression from teosinte into highland maize populations.
Historical Genomics of US Maize: Domestication and Modern Breeding
This document summarizes research on the historical genomics of maize evolution in North America. The study applied population genetic analysis to genome sequencing data from maize and teosinte lines to analyze patterns of evolution during domestication and modern breeding. They found distinct impacts of selection during these two epochs and identified candidate genes targeted during each. A separate analysis of a panel of 400 North American corn belt lines genotyped over time found decreasing genetic diversity and ancestral contributions, indicating selection shaped the genetic structure of modern maize.
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More from jrossibarra (19)
Adaptive evolution of genome size across altitudinal clines in maize
Adaptive evolution of genome size across altitudinal clines in maize
Gene flow and cross-incompatibility in maize and teosinte
Gene flow and cross-incompatibility in maize and teosinte
2015 SF Exploratorium Lecture: "Corn: Diversity and Origins"
2015 SF Exploratorium Lecture: "Corn: Diversity and Origins"
Introgression and the origin of maize in Mexico and the Southwest US
Introgression and the origin of maize in Mexico and the Southwest US
Population genetics of maize domestication, adaptation, and improvement
Population genetics of maize domestication, adaptation, and improvement
Bottlenecks -- some ramblings and a bit of data from maize PAGXXII
Bottlenecks -- some ramblings and a bit of data from maize PAGXXII
Historical Genomics of US Maize: Domestication and Modern Breeding
Historical Genomics of US Maize: Domestication and Modern Breeding
Advice for getting into grad school (in the biological sciences)
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In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
Video Streaming: Then, Now, and in the Future
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Essentials of Automations: The Art of Triggers and Actions in FME
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Full-RAG: A modern architecture for hyper-personalization
Mike Del Balso, CEO & Co-Founder at Tecton, presents "Full RAG," a novel approach to AI recommendation systems, aiming to push beyond the limitations of traditional models through a deep integration of contextual insights and real-time data, leveraging the Retrieval-Augmented Generation architecture. This talk will outline Full RAG's potential to significantly enhance personalization, address engineering challenges such as data management and model training, and introduce data enrichment with reranking as a key solution. Attendees will gain crucial insights into the importance of hyperpersonalization in AI, the capabilities of Full RAG for advanced personalization, and strategies for managing complex data integrations for deploying cutting-edge AI solutions.
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
20240609 QFM020 Irresponsible AI Reading List May 2024
Everything I found interesting about the irresponsible use of machine intelligence in May 2024
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
National Security Agency - NSA mobile device best practices
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
20240607 QFM018 Elixir Reading List May 2024
Everything I found interesting about the Elixir programming ecosystem in May 2024
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.“I’m still / I’m still / Chaining from the Block”
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
GraphSummit Singapore | Neo4j Product Vision & Roadmap - Q2 2024
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
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