scholarly journals Ecological adaptation in Atlantic herring is associated with large shifts in allele frequencies at hundreds of loci

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Fan Han ◽  
Minal Jamsandekar ◽  
Mats E Pettersson ◽  
Leyi Su ◽  
Angela P Fuentes-Pardo ◽  
...  
Keyword(s):  
Genetic Differentiation ◽  
North Atlantic ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Allele Frequencies ◽  
Ecological Adaptation ◽  
Genetic Adaptation ◽  
Atlantic Herring ◽  
Long Read

Atlantic herring is widespread in North Atlantic and adjacent waters and is one of the most abundant vertebrates on earth. This species is well suited to explore genetic adaptation due to minute genetic differentiation at selectively neutral loci. Here, we report hundreds of loci underlying ecological adaptation to different geographic areas and spawning conditions. Four of these represent megabase inversions confirmed by long read sequencing. The genetic architecture underlying ecological adaptation in herring deviates from expectation under a classical infinitesimal model for complex traits because of large shifts in allele frequencies at hundreds of loci under selection.

scholarly journals The genetic architecture underlying ecological adaptation in Atlantic herring is not consistent with the infinitesimal model

2020 ◽  
Author(s):  
Fan Han ◽  
Minal Jamsandekar ◽  
Mats E. Pettersson ◽  
Leyi Su ◽  
Angela Fuentes-Pardo ◽  
...  
Keyword(s):  
Genetic Differentiation ◽  
North Atlantic ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Allele Frequencies ◽  
Ecological Adaptation ◽  
Genetic Adaptation ◽  
Atlantic Herring ◽  
Long Read

AbstractAtlantic herring is widespread in North Atlantic and adjacent waters and is one of the most abundant vertebrates on earth. This species is well suited to explore genetic adaptation due to minute genetic differentiation at selectively neutral loci. Here we report hundreds of loci underlying ecological adaptation to different geographic areas and spawning conditions. Four of these represent megabase inversions confirmed by long read sequencing. The genetic architecture underlying ecological adaptation in the herring is in conflict with the infinitesimal model for complex traits because of the large shifts in allele frequencies at hundreds of loci under selection.

scholarly journals Author response: Ecological adaptation in Atlantic herring is associated with large shifts in allele frequencies at hundreds of loci

2020 ◽  
Author(s):  
Fan Han ◽  
Minal Jamsandekar ◽  
Mats E Pettersson ◽  
Leyi Su ◽  
Angela P Fuentes-Pardo ◽  
...  
Keyword(s):  
Allele Frequencies ◽  
Ecological Adaptation ◽  
Author Response ◽  
Atlantic Herring

scholarly journals A chromosome-level assembly of the Atlantic herring – detection of a supergene and other signals of selection

2019 ◽  
Author(s):  
Mats E. Pettersson ◽  
Christina M. Rochus ◽  
Fan Han ◽  
Junfeng Chen ◽  
Jason Hill ◽  
...  
Keyword(s):  
Genetic Differentiation ◽  
Genome Assembly ◽  
Large Scale ◽  
De Novo ◽  
Hybrid Approach ◽  
Ecological Adaptation ◽  
Atlantic Herring ◽  
Total Size ◽  
Bony Fishes ◽  
Chromosome Level

ABSTRACTThe Atlantic herring is a model species for exploring the genetic basis for ecological adaptation, due to its huge population size and extremely low genetic differentiation at selectively neutral loci. However, such studies have so far been hampered because of a highly fragmented genome assembly. Here, we deliver a chromosome-level genome assembly based on a hybrid approach combining ade novoPacBio assembly with Hi-C-supported scaffolding. The assembly comprises 26 autosomes with sizes ranging from 12.4 to 33.1 Mb and a total size, in chromosomes, of 726 Mb. The development of a high-resolution linkage map confirmed the global chromosome organization and the linear order of genomic segments along the chromosomes. A comparison between the herring genome assembly with other high-quality assemblies from bony fishes revealed few interchromosomal but frequent intrachromosomal rearrangements. The improved assembly makes the analysis of previously intractable large-scale structural variation more feasible; allowing, for example, the detection of a 7.8 Mb inversion on chromosome 12 underlying ecological adaptation. This supergene shows strong genetic differentiation between populations from the northern and southern parts of the species distribution. The chromosome-based assembly also markedly improves the interpretation of previously detected signals of selection, allowing us to reveal hundreds of independent loci associated with ecological adaptation in the Atlantic herring.

scholarly journals The genetic basis for ecological adaptation of the Atlantic herring revealed by genome sequencing

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Alvaro Martinez Barrio ◽  
Sangeet Lamichhaney ◽  
Guangyi Fan ◽  
Nima Rafati ◽  
Mats Pettersson ◽  
...  
Keyword(s):  
Genetic Differentiation ◽  
Genetic Architecture ◽  
Genetic Basis ◽  
Genetic Factors ◽  
Geographic Origin ◽  
Natural Populations ◽  
Ecological Adaptation ◽  
Timing Of Reproduction ◽  
Haplotype Blocks ◽  
Subdivided Populations

Ecological adaptation is of major relevance to speciation and sustainable population management, but the underlying genetic factors are typically hard to study in natural populations due to genetic differentiation caused by natural selection being confounded with genetic drift in subdivided populations. Here, we use whole genome population sequencing of Atlantic and Baltic herring to reveal the underlying genetic architecture at an unprecedented detailed resolution for both adaptation to a new niche environment and timing of reproduction. We identify almost 500 independent loci associated with a recent niche expansion from marine (Atlantic Ocean) to brackish waters (Baltic Sea), and more than 100 independent loci showing genetic differentiation between spring- and autumn-spawning populations irrespective of geographic origin. Our results show that both coding and non-coding changes contribute to adaptation. Haplotype blocks, often spanning multiple genes and maintained by selection, are associated with genetic differentiation.

scholarly journals Genetics of complex traits: prediction of phenotype, identification of causal polymorphisms and genetic architecture

2016 ◽  
Vol 283 (1835) ◽  
pp. 20160569 ◽  
Author(s):  
M. E. Goddard ◽  
K. E. Kemper ◽  
I. M. MacLeod ◽  
A. J. Chamberlain ◽  
B. J. Hayes
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Crop Breeding ◽  
Single Nucleotide ◽  
Genome Wide ◽  
Phenotype Identification

Complex or quantitative traits are important in medicine, agriculture and evolution, yet, until recently, few of the polymorphisms that cause variation in these traits were known. Genome-wide association studies (GWAS), based on the ability to assay thousands of single nucleotide polymorphisms (SNPs), have revolutionized our understanding of the genetics of complex traits. We advocate the analysis of GWAS data by a statistical method that fits all SNP effects simultaneously, assuming that these effects are drawn from a prior distribution. We illustrate how this method can be used to predict future phenotypes, to map and identify the causal mutations, and to study the genetic architecture of complex traits. The genetic architecture of complex traits is even more complex than previously thought: in almost every trait studied there are thousands of polymorphisms that explain genetic variation. Methods of predicting future phenotypes, collectively known as genomic selection or genomic prediction, have been widely adopted in livestock and crop breeding, leading to increased rates of genetic improvement.

scholarly journals RIL-StEp: epistasis analysis of rice recombinant inbred lines (RILs) reveals candidate interacting genes that control seed hull color and leaf chlorophyll content

2021 ◽  
Author(s):  
Toshiyuki Sakai ◽  
Akira Abe ◽  
Motoki Shimizu ◽  
Ryohei Terauchi
Keyword(s):  
Chlorophyll Content ◽  
Recombinant Inbred ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Recombinant Inbred Lines ◽  
Inbred Lines ◽  
Gene Interactions ◽  
Leaf Chlorophyll Content ◽  
Leaf Chlorophyll ◽  
Seed Hull

Abstract Characterizing epistatic gene interactions is fundamental for understanding the genetic architecture of complex traits. However, due to the large number of potential gene combinations, detecting epistatic gene interactions is computationally demanding. A simple, easy-to-perform method for sensitive detection of epistasis is required. Due to their homozygous nature, use of recombinant inbred lines (RILs) excludes the dominance effect of alleles and interactions involving heterozygous genotypes, thereby allowing detection of epistasis in a simple and interpretable model. Here, we present an approach called RIL-StEp (recombinant inbred lines stepwise epistasis detection) to detect epistasis using single nucleotide polymorphisms in the genome. We applied the method to reveal epistasis affecting rice (Oryza sativa) seed hull color and leaf chlorophyll content and successfully identified pairs of genomic regions that presumably control these phenotypes. This method has the potential to improve our understanding of the genetic architecture of various traits of crops and other organisms.

scholarly journals Better estimation of SNP heritability from summary statistics provides a new understanding of the genetic architecture of complex traits

2018 ◽  
Author(s):  
Doug Speed ◽  
David J Balding
Keyword(s):  
Complex Traits ◽  
Genetic Architecture ◽  
Large Scale ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Confounding Bias ◽  
Conserved Regions ◽  
Genome Wide ◽  
Variation Explained

LD Score Regression (LDSC) has been widely applied to the results of genome-wide association studies. However, its estimates of SNP heritability are derived from an unrealistic model in which each SNP is expected to contribute equal heritability. As a consequence, LDSC tends to over-estimate confounding bias, under-estimate the total phenotypic variation explained by SNPs, and provide misleading estimates of the heritability enrichment of SNP categories. Therefore, we present SumHer, software for estimating SNP heritability from summary statistics using more realistic heritability models. After demonstrating its superiority over LDSC, we apply SumHer to the results of 24 large-scale association studies (average sample size 121 000). First we show that these studies have tended to substantially over-correct for confounding, and as a result the number of genome-wide significant loci has under-reported by about 20%. Next we estimate enrichment for 24 categories of SNPs defined by functional annotations. A previous study using LDSC reported that conserved regions were 13-fold enriched, and found a further twelve categories with above 2-fold enrichment. By contrast, our analysis using SumHer finds that conserved regions are only 1.6-fold (SD 0.06) enriched, and that no category has enrichment above 1.7-fold. SumHer provides an improved understanding of the genetic architecture of complex traits, which enables more efficient analysis of future genetic data.

scholarly journals On Using Local Ancestry to Characterize the Genetic Architecture of Human Phenotypes: Genetic Regulation of Gene Expression in Multiethnic or Admixed Populations as a Model

2018 ◽  
Author(s):  
Yizhen Zhong ◽  
Minoli Perera ◽  
Eric R. Gamazon
Keyword(s):  
Gene Expression ◽  
Complex Traits ◽  
Genetic Architecture ◽  
Genetic Regulation ◽  
Regulation Of Gene Expression ◽  
Type I ◽  
Eqtl Mapping ◽  
Entire Genome ◽  
Local Ancestry ◽  
Heritability Estimation

AbstractBackgroundUnderstanding the nature of the genetic regulation of gene expression promises to advance our understanding of the genetic basis of disease. However, the methodological impact of use of local ancestry on high-dimensional omics analyses, including most prominently expression quantitative trait loci (eQTL) mapping and trait heritability estimation, in admixed populations remains critically underexplored.ResultsHere we develop a statistical framework that characterizes the relationships among the determinants of the genetic architecture of an important class of molecular traits. We estimate the trait variance explained by ancestry using local admixture relatedness between individuals. Using National Institute of General Medical Sciences (NIGMS) and Genotype-Tissue Expression (GTEx) datasets, we show that use of local ancestry can substantially improve eQTL mapping and heritability estimation and characterize the sparse versus polygenic component of gene expression in admixed and multiethnic populations respectively. Using simulations of diverse genetic architectures to estimate trait heritability and the level of confounding, we show improved accuracy given individual-level data and evaluate a summary statistics based approach. Furthermore, we provide a computationally efficient approach to local ancestry analysis in eQTL mapping while increasing control of type I and type II error over traditional approaches.ConclusionOur study has important methodological implications on genetic analysis of omics traits across a range of genomic contexts, from a single variant to a prioritized region to the entire genome. Our findings highlight the importance of using local ancestry to better characterize the heritability of complex traits and to more accurately map genetic associations.

Sign in / Sign up

Export Citation Format

Share Document