Barley Genomics: An Overview

Barley (Hordeum vulgare), first domesticated in the Near East, is a well-studied crop in terms of genetics, genomics, and breeding and qualifies as a model plant for Triticeae research. Recent advances made in barley genomics mainly include the following: (i) rapid accumulation of EST sequence data, (ii) growing number of studies on transcriptome, proteome, and metabolome, (iii) new modeling techniques, (iv) availability of genome-wide knockout collections as well as efficient transformation techniques, and (v) the recently started genome sequencing effort. These developments pave the way for a comprehensive functional analysis and understanding of gene expression networks linked to agronomically important traits. Here, we selectively review important technological developments in barley genomics and related fields and discuss the relevance for understanding genotype-phenotype relationships by using approaches such as genetical genomics and association studies. High-throughput genotyping platforms that have recently become available will allow the construction of high-density genetic maps that will further promote marker-assisted selection as well as physical map construction. Systems biology approaches will further enhance our knowledge and largely increase our abilities to design refined breeding strategies on the basis of detailed molecular physiological knowledge.

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Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program

Nature ◽

10.1038/s41586-021-03205-y ◽

2021 ◽

Vol 590 (7845) ◽

pp. 290-299 ◽

Cited By ~ 22

Author(s):

Daniel Taliun ◽

◽

Daniel N. Harris ◽

Michael D. Kessler ◽

Jedidiah Carlson ◽

...

Keyword(s):

Rare Variants ◽

Sequence Data ◽

Association Studies ◽

Genotype Imputation ◽

Genome Wide Association Studies ◽

Phenotypic Data ◽

Treatment And Prevention ◽

Genome Wide ◽

Diverse Backgrounds ◽

Unmapped Reads

AbstractThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.

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Whole-genome association mapping in elite inbred crop varietiesThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽

10.1139/g10-078 ◽

2010 ◽

Vol 53 (11) ◽

pp. 967-972 ◽

Cited By ~ 18

Author(s):

Robbie Waugh ◽

David Marshall ◽

Bill Thomas ◽

Jordi Comadran ◽

Joanne Russell ◽

...

Keyword(s):

Gene Pool ◽

Physical Map ◽

Association Studies ◽

Population Substructure ◽

Whole Genome ◽

Data Set ◽

Genome Wide ◽

Marker Loci ◽

Genome Association ◽

Whole Genome Association

We have previously shown that linkage disequilibrium (LD) in the elite cultivated barley ( Hordeum vulgare ) gene pool extends, on average, for <1–5 cM. Based on this information, we have developed a platform for whole genome association studies that comprises a collection of elite lines that we have characterized at 3060 genome-wide single nucleotide polymorphism (SNP) marker loci. Interrogating this data set shows that significant population substructure is present within the elite gene pool and that diversity and LD vary considerably across each of the seven barley chromosomes. However, we also show that a subpopulation comprised of only the two-rowed spring germplasm is less structured and well suited to whole genome association studies without the need for extensive statistical intervention to account for structure. At the current marker density, the two-rowed spring population is suited for fine mapping simple traits that are located outside of the genetic centromeres with a resolution that is sufficient for candidate gene identification by exploiting conservation of synteny with fully sequenced model genomes and the emerging barley physical map.

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Genome-Wide Meta-Analysis of Late-Onset Alzheimer's Disease Using Rare Variant Imputation in 324,809 Subjects Identifies Novel Rare Variant Locus NCK2: The International Genomics of Alzheimer's Project (IGAP)

10.1101/2021.03.14.21253553 ◽

2021 ◽

Author(s):

Adam C. Naj ◽

Ganna Leonenko ◽

Xueqiu Jian ◽

Benjamin Grenier-Boley ◽

Maria Carolina Dalmasso ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variant ◽

Late Onset ◽

Sequence Data ◽

Association Studies ◽

Meta Analysis ◽

Genome Wide Association Studies ◽

Genome Wide ◽

The Uk

Risk for late-onset Alzheimer's disease (LOAD) is driven by multiple loci primarily identified by genome-wide association studies, many of which are common variants with minor allele frequencies (MAF)>0.01. To identify additional common and rare LOAD risk variants, we performed a GWAS on 25,170 LOAD subjects and 41,052 cognitively normal controls in 44 datasets from the International Genomics of Alzheimer's Project (IGAP). Existing genotype data were imputed using the dense, high-resolution Haplotype Reference Consortium (HRC) r1.1 reference panel. Stage 1 associations of P<10-5 were meta-analyzed with the European Alzheimer's Disease Biobank (EADB) (n=20,301 cases; 21,839 controls) (stage 2 combined IGAP and EADB). An expanded meta-analysis was performed using a GWAS of parental AD/dementia history in the UK Biobank (UKBB) (n=35,214 cases; 180,791 controls) (stage 3 combined IGAP, EADB, and UKBB). Common variant (MAF≥0.01) associations were identified for 29 loci in stage 2, including novel genome-wide significant associations at TSPAN14 (P=2.33×10-12), SHARPIN (P=1.56×10-9), and ATF5/SIGLEC11 (P=1.03[mult]10-8), and newly significant associations without using AD proxy cases in MTSS1L/IL34 (P=1.80×10-8), APH1B (P=2.10×10-13), and CLNK (P=2.24×10-10). Rare variant (MAF<0.01) associations with genome-wide significance in stage 2 included multiple variants in APOE and TREM2, and a novel association of a rare variant (rs143080277; MAF=0.0054; P=2.69×10-9) in NCK2, further strengthened with the inclusion of UKBB data in stage 3 (P=7.17×10-13). Single-nucleus sequence data shows that NCK2 is highly expressed in amyloid-responsive microglial cells, suggesting a role in LOAD pathology.

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Sequencing of over 100,000 individuals identifies multiple genes and rare variants associated with Crohns disease susceptibility

10.1101/2021.06.15.21258641 ◽

2021 ◽

Author(s):

Aleksejs Sazonovs ◽

Christine R Stevens ◽

Guhan R Venkataraman ◽

Kai Yuan ◽

Brandon Avila ◽

...

Keyword(s):

Rare Variants ◽

Disease Risk ◽

Sequence Data ◽

Association Studies ◽

Genome Wide Association Studies ◽

Crohns Disease ◽

Biological Targets ◽

Genome Wide ◽

Coding Variants ◽

First Time

Genome-wide association studies (GWAS) have identified hundreds of loci associated with Crohns disease (CD); however, as with all complex diseases, deriving pathogenic mechanisms from these non-coding GWAS discoveries has been challenging. To complement GWAS and better define actionable biological targets, we analysed sequence data from more than 30,000 CD cases and 80,000 population controls. We observe rare coding variants in established CD susceptibility genes as well as ten genes where coding variation directly implicates the gene in disease risk for the first time.

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Genome-wide association studies for methane emission and ruminal volatile fatty acids using Holstein cattle sequence data

10.21203/rs.2.20637/v2 ◽

2020 ◽

Author(s):

Ali Jalil Sarghale ◽

Mohammad Moradi Shahrebabak ◽

Hossein Moradi Shahrebabak ◽

Ardeshir Nejati Javaremi ◽

Mahdi Saatchi ◽

...

Keyword(s):

Methane Emission ◽

Feed Intake ◽

Volatile Fatty Acids ◽

Sequence Data ◽

Association Studies ◽

Olfactory Receptors ◽

Significant Snps ◽

Valeric Acid ◽

Genome Wide Association Studies ◽

Genome Wide

Abstract Background: Methane emission by ruminants has contributed considerably to the global warming and understanding the genomic architecture of methane production may help the livestock producers to reduce the methane emission from the livestock production system. The goal of our study was to identify genomic regions affecting the predicted methane emission (PME) from volatile fatty acids (VFAs) indicators and VFA traits using imputed whole-genome sequence data in Iranian Holstein cattle. Results: Based on the significant-association threshold (p < 5 × 10−8), 33 single nucleotide polymorphisms (SNPs) were detected for PME per kg milk (n=2), PME per kg fat (n=14), and valeric acid (n=17). Besides, 69 genes were identified for valeric acid (n=18), PME per kg milk (n=4) and PME per kg fat (n=47) that were located within 1 Mb of significant SNPs. Based on the gene ontology (GO) term analysis, six promising candidate genes were significantly clustered in organelle organization (GO:0004984, p = 3.9 × 10-2) for valeric acid, and 17 candidate genes significantly clustered in olfactory receptors activity (GO:0004984, p = 4 × 10-10) for PME traits. Annotation results revealed 31 quantitative trait loci (QTLs) for milk yield and its components, body weight, and residual feed intake within 1 Mb of significant SNPs. Conclusions: Our results identified 33 SNPs associated with PME and valeric acid traits, as well as 17 olfactory receptors activity genes for PME traits related to food preference and feed intake. Identified SNPs in this study were close to 31 QTLs for milk yield and its components, body weight, and residual feed intake traits. In addition, these traits had high correlations with PME trait. Overall, our findings suggest that marker-assisted and genomic selection could be used to improve the difficult and expensive-to-measure phenotypes such as PME. Moreover, prediction of methane emission by VFA indicators could be useful for increasing the size of the reference population required in genome-wide association studies and genomic selection.

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Linkage disequilibrium maps for European and African populations constructed from whole genome sequence data

Scientific Data ◽

10.1038/s41597-019-0227-y ◽

2019 ◽

Vol 6 (1) ◽

Cited By ~ 1

Author(s):

Alejandra Vergara-Lope ◽

M. Reza Jabalameli ◽

Clare Horscroft ◽

Sarah Ennis ◽

Andrew Collins ◽

...

Keyword(s):

Linkage Disequilibrium ◽

Genome Sequence ◽

Sequence Data ◽

Association Studies ◽

Large Population ◽

Whole Genome Sequence ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Whole Genome ◽

Genome Wide

Abstract Quantification of linkage disequilibrium (LD) patterns in the human genome is essential for genome-wide association studies, selection signature mapping and studies of recombination. Whole genome sequence (WGS) data provides optimal source data for this quantification as it is free from biases introduced by the design of array genotyping platforms. The Malécot-Morton model of LD allows the creation of a cumulative map for each choromosome, analogous to an LD form of a linkage map. Here we report LD maps generated from WGS data for a large population of European ancestry, as well as populations of Baganda, Ethiopian and Zulu ancestry. We achieve high average genetic marker densities of 2.3–4.6/kb. These maps show good agreement with prior, low resolution maps and are consistent between populations. Files are provided in BED format to allow researchers to readily utilise this resource.

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Addressing the Challenges of Detecting Epistasis in Genome-Wide Association Studies of Common Human Diseases Using Biological Expert Knowledge

Handbook of Research on Computational and Systems Biology ◽

10.4018/978-1-60960-491-2.ch006 ◽

2011 ◽

pp. 128-147

Author(s):

Kristine A. Pattin ◽

Jason H. Moore

Keyword(s):

Expert Knowledge ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Nucleotide Polymorphisms ◽

Protein Protein Interaction ◽

Genome Wide ◽

Technological Developments ◽

Or Gene ◽

High Dimensional Datasets

Recent technological developments in the field of genetics have given rise to an abundance of research tools, such as genome-wide genotyping, that allow researchers to conduct genome-wide association studies (GWAS) for detecting genetic variants that confer increased or decreased susceptibility to disease. However, discovering epistatic, or gene-gene, interactions in high dimensional datasets is a problem due to the computational complexity that results from the analysis of all possible combinations of single-nucleotide polymorphisms (SNPs). A recently explored approach to this problem employs biological expert knowledge, such as pathway or protein-protein interaction information, to guide an analysis by the selection or weighting of SNPs based on this knowledge. Narrowing the evaluation to gene combinations that have been shown to interact experimentally provides a biologically concise reason why those two genes may be detected together statistically. This chapter discusses the challenges of discovering epistatic interactions in GWAS and how biological expert knowledge can be used to facilitate genome-wide genetic studies.

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Development of Genome-wide SSR Markers for Physical Map Construction with PCR-based Polymorphic SSRs in Jute (Corchorus Spp.)

Tropical Plant Biology ◽

10.1007/s12042-021-09301-7 ◽

2021 ◽

Author(s):

Sylvain Niyitanga ◽

Jiayu Yao ◽

Aminu kurawa Ibrahim ◽

Muhammad Zohaib Afzal ◽

Siyuan Chen ◽

...

Keyword(s):

Ssr Markers ◽

Physical Map ◽

Polymorphic Ssrs ◽

Map Construction ◽

Genome Wide

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SeqBreed: a python tool to evaluate genomic prediction in complex scenarios

10.1101/748624 ◽

2019 ◽

Author(s):

M. Pérez-Enciso ◽

L. C. Ramírez-Ayala ◽

L.M. Zingaretti

Keyword(s):

Genomic Prediction ◽

Predictive Accuracy ◽

Sequence Data ◽

Association Studies ◽

Single Step ◽

Genome Wide Association ◽

Drosophila Genome ◽

Genome Wide Association Studies ◽

Complex Phenotypes ◽

Genome Wide

AbstractBackgroundGenomic Prediction (GP) is the procedure whereby molecular information is used to predict complex phenotypes. Although GP can significantly enhance predictive accuracy, it can be expensive and difficult to implement. To help in designing optimum experiments, including genome wide association studies and genomic selection experiments, we have developed SeqBreed, a generic and flexible python3 forward simulator.ResultsSeqBreed accommodates sex and mitochondrion chromosomes as well as autopolyploidy. It can simulate any number of complex phenotypes determined by any number of causal loci. SeqBreed implements several GP methods, including single step GBLUP. We demonstrate its functionality with Drosophila Genome Reference Panel (DGRP) sequence data and with tetraploid potato genotypes.ConclusionsSeqBreed is a flexible and easy to use tool appropriate for optimizing GP or genome wide association studies. It incorporates some of the most popular GP methods and includes several visualization tools. Code is open and can be freely modified. Software, documentation and examples are available at https://github.com/miguelperezenciso/SeqBreed.

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