As a living information and communications system, the genome encodes patterns in single nucleotide polymorphisms (SNPs) reflecting human adaptation that optimizes population survival in differing environments. This p...As a living information and communications system, the genome encodes patterns in single nucleotide polymorphisms (SNPs) reflecting human adaptation that optimizes population survival in differing environments. This paper mathematically models environmentally induced adaptive forces that quantify changes in the distribution of SNP frequencies between populations. We make direct connections between biophysical methods (e.g. minimizing genomic free energy) and concepts in population genetics. Our unbiased computer program scanned a large set of SNPs in the major histocompatibility complex region and flagged an altitude dependency on a SNP associated with response to oxygen deprivation. The statistical power of our double-blind approach is demonstrated in the flagging of mathematical functional correlations of SNP information-based potentials in multiple populations with specific environmental parameters. Furthermore, our approach provides insights for new discoveries on the biology of common variants. This paper demonstrates the power of biophysical modeling of population diversity for better understanding genome-environment interactions in biological phenomenon.展开更多
The human genome is a complex, dynamic information system that encodes principles of life and living systems. These principles are incorporated in the structure of human genome sequence variation and are foundational ...The human genome is a complex, dynamic information system that encodes principles of life and living systems. These principles are incorporated in the structure of human genome sequence variation and are foundational for the continuity of life and human survival. Using first principles of thermodynamics and statistical physics, we have developed analogous “genodynamic tools” for population genomic studies. Characterizing genomic information through the lens of physics has allowed us to develop energy measures for modeling genome-environment interactions. In developing biophysical parameters for genome-environment homeostasis, we found that stable genomic free energy trades off low genomic energy (genomic conservation and increased order) and high genomic entropy (genomic variation) with an environmental potential that drives the variation. In our approach, we assert that common variants are dynamic sites in the genome of a population and that the stability of whole genome adaptation is reflected in the frequencies of maintained diversity in common variants for the population in its environment. In this paper, we address the relativity of whole genome adaptation towards homeostasis. By this we mean that adaptive forces are directly reflected in the frequency distribution of alleles and/or haplotypes of the population relative to its environment, with adaptive forces driving the genome towards homeostasis. The use of genomic energy units as a biophysical metric in DNA sequence variation analyses provides new insights into the foundations of population biology and diversity. Using our biophysical tools, population differences directly reflect the adaptive influences of the environment on populations.展开更多
Understanding the genetic mechanism of cold adaptation in cashmere goats and dairy goats is very important to improve their production performance.The purpose of this study was to comprehensively analyze the genetic b...Understanding the genetic mechanism of cold adaptation in cashmere goats and dairy goats is very important to improve their production performance.The purpose of this study was to comprehensively analyze the genetic basis of goat adaptation to cold environments,clarify the impact of environmental factors on genome diversity,and lay the foundation for breeding goat breeds to adapt to climate change.A total of 240 dairy goats were subjected to genome resequencing,and the whole genome sequencing data of 57 individuals from 6 published breeds were incorporated.By integrating multiple approaches such as phylogenetic analysis,population structure analysis,gene flow and population history exploration,selection signal analysis,and genome-environment association analysis,an in-depth investigation was carried out.Phylogenetic analysis unraveled the genetic relationships and differentiation patterns among dairy goats and other goat breeds.Through signal analysis(θπ,FST,XP-CLR),we identified numerous candidate genes associated with cold adaptation in dairy goats(STRIP1,ALX3,HTR4,NTRK2,MRPL11,PELI3,DPP3,BBS1)and cashmere goats(MED12L,MARC2,MARC1,DSG3,C6H4orf22,CHD7,MYPN,KIAA0825,MITF).Genomeenvironment association(GEA)analysis confirmed the link between these genes and environmental factors.Moreover,a detailed analysis of the critical genes C6H4orf22 and STRIP1 demonstrated their significant roles in the geographical variations of cold adaptation and allele frequency differences among different breeds.This study contributes to understanding the genetic basis of cold adaptation,providing crucial theoretical support for precision breeding programs aimed at improving production performance in cold regions by leveraging adaptive alleles,thereby ensuring sustainable animal husbandry.展开更多
Populations are continually adapting to their environment.Knowledge of which populations and individuals harbor unique and agriculturally useful variations has the potential to accelerate crop adaptation to the increa...Populations are continually adapting to their environment.Knowledge of which populations and individuals harbor unique and agriculturally useful variations has the potential to accelerate crop adaptation to the increasingly challenging environments predicted for the coming century.Landscape genomics,which identifies associations between environmental and genomic variation,provides a means for obtaining this knowledge.However,despite extensive efforts to assemble and characterize ex situ collections of crops and their wild relatives,gaps remain in the genomic and environmental datasets needed to robustly implement this approach.This article outlines the history of landscape genomics,which,to date,has mainly been used in conservation and evolutionary studies,provides an overview of crops and wild relative collections that have the necessary data for implementation and identifies areas where new data genera-tion is needed.We find that 60%of the crops covered by the International Treaty on Plant Genetic Re-sources for Food and Agriculture lack the data necessary to conduct this kind of analysis,necessitating identification of crops in need of more collections,sequencing,or phenotyping.By highlighting these as-pects,we aim to help develop agricultural landscape genomics as a sub-discipline that brings together evolutionary genetics,landscape ecology,and plant breeding,ultimately enhancing the development of resilient and adaptable crops for future environmental challenges.展开更多
文摘As a living information and communications system, the genome encodes patterns in single nucleotide polymorphisms (SNPs) reflecting human adaptation that optimizes population survival in differing environments. This paper mathematically models environmentally induced adaptive forces that quantify changes in the distribution of SNP frequencies between populations. We make direct connections between biophysical methods (e.g. minimizing genomic free energy) and concepts in population genetics. Our unbiased computer program scanned a large set of SNPs in the major histocompatibility complex region and flagged an altitude dependency on a SNP associated with response to oxygen deprivation. The statistical power of our double-blind approach is demonstrated in the flagging of mathematical functional correlations of SNP information-based potentials in multiple populations with specific environmental parameters. Furthermore, our approach provides insights for new discoveries on the biology of common variants. This paper demonstrates the power of biophysical modeling of population diversity for better understanding genome-environment interactions in biological phenomenon.
文摘The human genome is a complex, dynamic information system that encodes principles of life and living systems. These principles are incorporated in the structure of human genome sequence variation and are foundational for the continuity of life and human survival. Using first principles of thermodynamics and statistical physics, we have developed analogous “genodynamic tools” for population genomic studies. Characterizing genomic information through the lens of physics has allowed us to develop energy measures for modeling genome-environment interactions. In developing biophysical parameters for genome-environment homeostasis, we found that stable genomic free energy trades off low genomic energy (genomic conservation and increased order) and high genomic entropy (genomic variation) with an environmental potential that drives the variation. In our approach, we assert that common variants are dynamic sites in the genome of a population and that the stability of whole genome adaptation is reflected in the frequencies of maintained diversity in common variants for the population in its environment. In this paper, we address the relativity of whole genome adaptation towards homeostasis. By this we mean that adaptive forces are directly reflected in the frequency distribution of alleles and/or haplotypes of the population relative to its environment, with adaptive forces driving the genome towards homeostasis. The use of genomic energy units as a biophysical metric in DNA sequence variation analyses provides new insights into the foundations of population biology and diversity. Using our biophysical tools, population differences directly reflect the adaptive influences of the environment on populations.
基金supported by the Genome Sequence Archiv in National Genomics Data Center,China National Center for Bioinformation/Beijing Institute of Genomics(CRA017705)supported the discovers could been obtained from the corresponding authors.
文摘Understanding the genetic mechanism of cold adaptation in cashmere goats and dairy goats is very important to improve their production performance.The purpose of this study was to comprehensively analyze the genetic basis of goat adaptation to cold environments,clarify the impact of environmental factors on genome diversity,and lay the foundation for breeding goat breeds to adapt to climate change.A total of 240 dairy goats were subjected to genome resequencing,and the whole genome sequencing data of 57 individuals from 6 published breeds were incorporated.By integrating multiple approaches such as phylogenetic analysis,population structure analysis,gene flow and population history exploration,selection signal analysis,and genome-environment association analysis,an in-depth investigation was carried out.Phylogenetic analysis unraveled the genetic relationships and differentiation patterns among dairy goats and other goat breeds.Through signal analysis(θπ,FST,XP-CLR),we identified numerous candidate genes associated with cold adaptation in dairy goats(STRIP1,ALX3,HTR4,NTRK2,MRPL11,PELI3,DPP3,BBS1)and cashmere goats(MED12L,MARC2,MARC1,DSG3,C6H4orf22,CHD7,MYPN,KIAA0825,MITF).Genomeenvironment association(GEA)analysis confirmed the link between these genes and environmental factors.Moreover,a detailed analysis of the critical genes C6H4orf22 and STRIP1 demonstrated their significant roles in the geographical variations of cold adaptation and allele frequency differences among different breeds.This study contributes to understanding the genetic basis of cold adaptation,providing crucial theoretical support for precision breeding programs aimed at improving production performance in cold regions by leveraging adaptive alleles,thereby ensuring sustainable animal husbandry.
文摘Populations are continually adapting to their environment.Knowledge of which populations and individuals harbor unique and agriculturally useful variations has the potential to accelerate crop adaptation to the increasingly challenging environments predicted for the coming century.Landscape genomics,which identifies associations between environmental and genomic variation,provides a means for obtaining this knowledge.However,despite extensive efforts to assemble and characterize ex situ collections of crops and their wild relatives,gaps remain in the genomic and environmental datasets needed to robustly implement this approach.This article outlines the history of landscape genomics,which,to date,has mainly been used in conservation and evolutionary studies,provides an overview of crops and wild relative collections that have the necessary data for implementation and identifies areas where new data genera-tion is needed.We find that 60%of the crops covered by the International Treaty on Plant Genetic Re-sources for Food and Agriculture lack the data necessary to conduct this kind of analysis,necessitating identification of crops in need of more collections,sequencing,or phenotyping.By highlighting these as-pects,we aim to help develop agricultural landscape genomics as a sub-discipline that brings together evolutionary genetics,landscape ecology,and plant breeding,ultimately enhancing the development of resilient and adaptable crops for future environmental challenges.
