Development of an SNP Marker Set for Marker-Assisted Backcrossing Using Genotyping-By-Sequencing in Tetraploid Perilla

Abstract High-quality molecular markers are essential for marker-assisted selection to accelerate breeding progress. Compared with diploid species, recently diverged polyploid crop species tend to have highly similar homeologous subgenomes, which is expected to limit the development of broadly applicable locus-specific single-nucleotide polymorphism (SNP) assays. Furthermore, it is particularly challenging to make genome-wide marker sets for species that lack a reference genome. Here, we report the development of a genome-wide set of kompetitive allele specific PCR (KASP) markers for marker-assisted recurrent selection (MARS) in the tetraploid minor crop perilla. To find locus-specific SNP markers across the perilla genome, we used genotyping-by-sequencing (GBS) to construct linkage maps of two F2 populations. The two resulting high-resolution linkage maps comprised 2,326 and 2,454 SNP markers that spanned a total genetic distance of 2,133 cM across 16 linkage groups and 2,169 cM across 21 linkage groups, respectively. We then obtained a final genetic map consisting of 22 linkage groups with 1,123 common markers from the two genetic maps. We selected 96 genome-wide markers for MARS and confirmed the accuracy of markers in the two F2 populations using a high-throughput Fluidigm system. We confirmed that 91.8% of the SNP genotyping results from the Fluidigm assay were the same as the results obtained through GBS. These results provide a foundation for marker-assisted backcrossing and the development of new varieties of perilla.

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SNP discovery by amplicon sequencing and multiplex SNP genotyping in the allopolyploid species Brassica napusThis 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/g10-079 ◽

2010 ◽

Vol 53 (11) ◽

pp. 948-956 ◽

Cited By ~ 35

Author(s):

G. Durstewitz ◽

A. Polley ◽

J. Plieske ◽

H. Luerssen ◽

E. M. Graner ◽

...

Keyword(s):

Genetic Analysis ◽

Oilseed Rape ◽

Expressed Sequence Tag ◽

Diploid Species ◽

Amplicon Sequencing ◽

Snp Markers ◽

Snp Analysis ◽

Genome Wide ◽

A Genome ◽

Illumina Goldengate

Oilseed rape ( Brassica napus ) is an allotetraploid species consisting of two genomes, derived from B. rapa (A genome) and B. oleracea (C genome). The presence of these two genomes makes single nucleotide polymorphism (SNP) marker identification and SNP analysis more challenging than in diploid species, as for a given locus usually two versions of a DNA sequence (based on the two ancestral genomes) have to be analyzed simultaneously during SNP identification and analysis. One hundred amplicons derived from expressed sequence tag (ESTs) were analyzed to identify SNPs in a panel of oilseed rape varieties and within two sister species representing the ancestral genomes. A total of 604 SNPs were identified, averaging one SNP in every 42 bp. It was possible to clearly discriminate SNPs that are polymorphic between different plant varieties from SNPs differentiating the two ancestral genomes. To validate the identified SNPs for their use in genetic analysis, we have developed Illumina GoldenGate assays for some of the identified SNPs. Through the analysis of a number of oilseed rape varieties and mapping populations with GoldenGate assays, we were able to identify a number of different segregation patterns in allotetraploid oilseed rape. The majority of the identified SNP markers can be readily used for genetic mapping, showing that amplicon sequencing and Illumina GoldenGate assays can be used to reliably identify SNP markers in tetraploid oilseed rape and to convert them into successful SNP assays that can be used for genetic analysis.

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Accounting for Errors in Low Coverage High-Throughput Sequencing Data when Constructing Genetic Maps using Biparental Outcrossed Populations

10.1101/249722 ◽

2018 ◽

Author(s):

Timothy P. Bilton ◽

Matthew R. Schofield ◽

Michael A. Black ◽

David Chagné ◽

Phillip L. Wilcox ◽

...

Keyword(s):

High Throughput ◽

Genetic Linkage ◽

High Throughput Sequencing ◽

Diploid Species ◽

Genotyping By Sequencing ◽

Genetic Maps ◽

Linkage Maps ◽

Sequencing Data ◽

Genetic Linkage Maps ◽

Low Coverage

ABSTRACTNext generation sequencing is an efficient method that allows for substantially more markers than previous technologies, providing opportunities for building high density genetic linkage maps, which facilitate the development of non-model species’ genomic assemblies and the investigation of their genes. However, constructing genetic maps using data generated via high-throughput sequencing technology (e.g., genotyping-by-sequencing) is complicated by the presence of sequencing errors and genotyping errors resulting from missing parental alleles due to low sequencing depth. If unaccounted for, these errors lead to inflated genetic maps. In addition, map construction in many species is performed using full-sib family populations derived from the outcrossing of two individuals, where unknown parental phase and varying segregation types further complicate construction. We present a new methodology for modeling low coverage sequencing data in the construction of genetic linkage maps using full-sib populations of diploid species, implemented in a package called GUSMap. Our model is based on an extension of the Lander-Green hidden Markov model that accounts for errors present in sequencing data. Results show that GUSMap was able to give accurate estimates of the recombination fractions and overall map distance, while most existing mapping packages produced inflated genetic maps in the presence of errors. Our results demonstrate the feasibility of using low coverage sequencing data to produce genetic maps without requiring extensive filtering of potentially erroneous genotypes, provided that the associated errors are correctly accounted for in the model.

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Construction of high-density genetic map and QTL mapping in Nicotiana tabacum backcrossing BC4F3 population using whole-genome sequencing

Czech Journal of Genetics and Plant Breeding ◽

10.17221/8/2021-cjgpb ◽

2021 ◽

Author(s):

Zhijun Tong ◽

Sanjie Jiang ◽

Weiming He ◽

Xuejun Chen ◽

Lixin Yin ◽

...

Keyword(s):

High Throughput Sequencing ◽

Snp Markers ◽

High Density ◽

Genetic Maps ◽

Recurrent Parent ◽

Sequencing Data ◽

High Throughput Sequencing Data ◽

A Genome ◽

Bc4f3 Population ◽

Marker Assisted Backcrossing

Backcrossing is a powerful tool for plant breeding. The improved marker-assisted backcrossing intends to transfer targeted genes or quantitative trait loci (QTLs) of interest from a donor parent into a recurrent parent. In this study, a tobacco BC4F3 population was generated using Y3 and K326 as hybrid parents and YF1-1 as F1 parents. High-throughput sequencing data of 381 pedigree populations were used to construct high-density genetic maps containing 24 142 high-quality single nucleotide polymorphism (SNP) markers with an average genetic distance of 0.59 cM. A genome module analysis was then performed for all the offspring. A total of forty-three candidate QTLs for six agronomics traits were identified. This study provides original biomarkers for tobacco breeding and offers clues for prospective backcrossing applications in other plants.

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Identification of resistance loci against new pathotypes of Plasmodiophora brassicae in Brassica napus based on genome-wide association mapping

Scientific Reports ◽

10.1038/s41598-021-85836-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Abdulsalam Dakouri ◽

Mebarek Lamara ◽

Md. Masud Karim ◽

Jinghe Wang ◽

Qilin Chen ◽

...

Keyword(s):

Brassica Napus ◽

Plasmodiophora Brassicae ◽

Genetic Resistance ◽

Genotyping By Sequencing ◽

Mixed Linear Model ◽

Snp Markers ◽

Sources Of Resistance ◽

Genome Wide ◽

Population Structure Analysis ◽

A Genome

AbstractGenetic resistance is a successful strategy for management of clubroot (Plasmodiophora brassicae) of brassica crops, but resistance can break down quickly. Identification of novel sources of resistance is especially important when new pathotypes arise. In the current study, the reaction of 177 accessions of Brassica napus to four new, virulent pathotypes of P. brassicae was assessed. Each accession was genotyped using genotyping by sequencing to identify and map novel sources of clubroot resistance using mixed linear model (MLM) analysis. The majority of accessions were highly susceptible (70–100 DSI), but a few accessions exhibited strong resistance (0–20 DSI) to pathotypes 5X (21 accessions), 3A (8), 2B (7), and 3D (15), based on the Canadian Clubroot Differential system. In total, 301,753 SNPs were mapped to 19 chromosomes. Population structure analysis indicated that the 177 accessions belong to seven major populations. SNPs were associated with resistance to each pathotype using MLM. In total, 13 important SNP loci were identified, with 9 SNPs mapped to the A-genome and 4 to the C-genome. The SNPs were associated with resistance to pathotypes 5X (2 SNPs), 3A (4), 2B (5) and 3D (6). A Blast search of 1.6 Mb upstream and downstream from each SNP identified 13 disease-resistance genes or domains. The distance between a SNP locus and the nearest resistance gene ranged from 0.04 to 0.74 Mb. The resistant lines and SNP markers identified in this study can be used to breed for resistance to the most prevalent new pathotypes of P. brassicae in Canada.

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Genome-wide association for heifer reproduction and calf performance traits in beef cattle

Genome ◽

10.1139/gen-2015-0031 ◽

2015 ◽

Vol 58 (12) ◽

pp. 549-557 ◽

Cited By ~ 5

Author(s):

Everestus C. Akanno ◽

Graham Plastow ◽

Carolyn Fitzsimmons ◽

Stephen P. Miller ◽

Vern Baron ◽

...

Keyword(s):

Beef Cattle ◽

Genome Wide Association Study ◽

Average Daily Gain ◽

Snp Markers ◽

Genome Wide Association ◽

Research Centre ◽

Genome Wide ◽

A Genome ◽

Starting Point ◽

And Performance

The aim of this study was to identify SNP markers that associate with variation in beef heifer reproduction and performance of their calves. A genome-wide association study was performed by means of the generalized quasi-likelihood score (GQLS) method using heifer genotypes from the BovineSNP50 BeadChip and estimated breeding values for pre-breeding body weight (PBW), pregnancy rate (PR), calving difficulty (CD), age at first calving (AFC), calf birth weight (BWT), calf weaning weight (WWT), and calf pre-weaning average daily gain (ADG). Data consisted of 785 replacement heifers from three Canadian research herds, namely Brandon Research Centre, Brandon, Manitoba, University of Alberta Roy Berg Kinsella Ranch, Kinsella, Alberta, and Lacombe Research Centre, Lacombe, Alberta. After applying a false discovery rate correction at a 5% significance level, a total of 4, 3, 3, 9, 6, 2, and 1 SNPs were significantly associated with PBW, PR, CD, AFC, BWT, WWT, and ADG, respectively. These SNPs were located on chromosomes 1, 5–7, 9, 13–16, 19–21, 24, 25, and 27–29. Chromosomes 1, 5, and 24 had SNPs with pleiotropic effects. New significant SNPs that impact functional traits were detected, many of which have not been previously reported. The results of this study support quantitative genetic studies related to the inheritance of these traits, and provides new knowledge regarding beef cattle quantitative trait loci effects. The identification of these SNPs provides a starting point to identify genes affecting heifer reproduction traits and performance of their calves (BWT, WWT, and ADG). They also contribute to a better understanding of the biology underlying these traits and will be potentially useful in marker- and genome-assisted selection and management.

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Genome-wide association analysis of resistance to Pseudoperonospora cubensis in citron watermelon

Plant Disease ◽

10.1094/pdis-08-21-1611-re ◽

2021 ◽

Author(s):

Dennis Katuuramu ◽

Sandra Branham ◽

Amnon Levi ◽

Patrick Wechter

Keyword(s):

Candidate Genes ◽

Genome Wide Association Study ◽

Citrullus Lanatus ◽

Phenotypic Variability ◽

Germplasm Collection ◽

Snp Markers ◽

Genome Wide Association ◽

Pseudoperonospora Cubensis ◽

Genome Wide ◽

A Genome

Cultivated sweet watermelon (Citrullus lanatus) is an important vegetable crop for millions of people around the world. There are limited sources of resistance to economically important diseases within C. lanatus, whereas Citrullus amarus has a reservoir of traits that can be exploited to improve C. lanatus for resistance to biotic and abiotic stresses. Cucurbit downy mildew (CDM), caused by Pseudoperonospora cubensis, is an emerging threat to watermelon production. We screened 122 C. amarus accessions for resistance to CDM over two tests (environments). The accessions were genotyped by whole-genome resequencing to generate 2,126,759 single nucleotide polymorphic (SNP) markers. A genome-wide association study was deployed to uncover marker-trait associations and identify candidate genes underlying resistance to CDM. Our results indicate the presence of wide phenotypic variability (1.1 - 57.8%) for leaf area infection, representing a 50.7-fold variation for CDM resistance across the C. amarus germplasm collection. Broad-sense heritability estimate was 0.55, implying the presence of moderate genetic effects for resistance to CDM. The peak SNP markers associated with resistance to P. cubensis were located on chromosomes Ca03, Ca05, Ca07, and Ca11. The significant SNP markers accounted for up to 30% of the phenotypic variation and were associated with promising candidate genes encoding disease resistance proteins, leucine-rich repeat receptor-like protein kinase, and WRKY transcription factor. This information will be useful in understanding the genetic architecture of the P. cubensis-Citrullus spp. patho-system as well as development of resources for genomics-assisted breeding for resistance to CDM in watermelon.

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Big fish, little fish: a multi-omics investigation of growth traits in silver trevally (Pseudocaranx georgianus – araara)

10.26686/wgtn.16698571 ◽

2021 ◽

Author(s):

◽

Noémie Valenza-Troubat

Keyword(s):

New Zealand ◽

Linkage Mapping ◽

Genetic Architecture ◽

Genetic Basis ◽

Growth Traits ◽

Expression Patterns ◽

Linkage Groups ◽

Phenotypic Data ◽

Genome Wide ◽

A Genome

Understanding the relationship between DNA sequence variation and the diversity of observable traits across the tree of life is a central research theme in biology. In all organisms, most traits vary continuously between individuals. Explaining the genetic basis of this quantitative variation requires disentangling genetic from non-genetic factors, as well as their interactions. The identification of causal genetic variants yields fundamental insights into how evolution creates diversity across the tree of life. Ultimately, this information can be used for medical, environmental and agricultural applications. Aquaculture is an industry that is experiencing significant global growth and is benefiting from the advances of genomic research. Genomic information helps to improve complex commercial phenotypes such as growth traits, which are easily quantified visually, but influenced by polygenes and multiple environmental factors, such as temperature. In the context of a global food crisis and environmental change, there is an urgent need not only to understand which genetic variants are potential candidates for selection gains, but also how the architecture of these traits are composed (e.g. monogenes, polygenes) and how they are influenced by and interact with the environment. The overall goal of this thesis research was to generate a genome-wide multi-omics dataset matched with exhaustive phenotypic information derived from a F0-F1 pedigree to investigate the quantitative genetic basis of growth in the New Zealand silver trevally (Pseudocaranx georgianus). These data were used to identify genomic regions that co-segregate with growth traits, and to describe the regulation of the genes involved in response to temperature fluctuations. The findings of this research helped gain fundamental insights into the genotype–phenotype map in an important teleost species and understand its ability to dynamically respond to temperature variations. This will ultimately support the establishment of a genomics-informed New Zealand aquaculture breeding programme. Chapter 1 of this thesis provides an overview of how genes interact with the environment to produce various growth phenotypes and how an understanding of this is important in aquaculture. This first chapter provides the deeper context for the research in subsequent data chapters. Chapter 2 describes the study population, the collection of phenotypic and genotypic data, and a first description of the genetic parameters of growth traits in trevally. A combination of Whole Genome Sequencing (WGS) and Genotyping-By-Sequencing (GBS) techniques were used to generate 60 thousand Single Nucleotide Polymorphism (SNP) markers for individuals in a two-generation pedigree. Together with phenotypic data, the genotyping data were used to reconstruct the pedigree, measure inbreeding levels, and estimate heritability for 10 growth traits. Parents were identified for 63% of the offspring and successful pedigree reconstruction indicated highly uneven contributions of each parent, and between the sexes, to the subsequent generation. The average inbreeding levels did not change between generations, but were significantly different between families. Growth patterns were found to be similar to that of other carangids and subject to seasonal variations. Heritability as well as genetic and phenotypic correlations were estimated using both a pedigree and a genomic relatedness matrix. All growth trait heritability estimates and correlations were found to be consistently high and positively correlated to each other. In Chapter 3, genotypic and phenotypic data were used to carry out linkage mapping and a genome-wide association study (GWAS) to map quantitative trait loci (QTLs) associated with growth differences in the F1 population. A linkage map was generated using the largest family, which allowed to scan for rare variants associated with the traits. The linkage map reported in this thesis is the first one for the Pseudocaranx genus and one of the densest for the carangid family. It included 19,861 SNPs contained in 24 linkage groups, which correspond to the 24 trevally chromosomes. Eight significant QTLs associated with height, length and weight were discovered on three linkage groups. Using GWAS, 113 SNPs associated with nine traits were identified and 29 genetic growth hot spots were uncovered. Two of the GWAS markers co-located with the QTLs discovered with the linkage mapping analysis. This demonstrates that combining QTL mapping and GWAS represents a powerful approach for the identification and validation of loci controlling complex phenotypes, such as growth, and provides important insights into the genetic architecture of these traits. Chapter 4, the last data chapter, investigates plasticity in gene expression patterns and growth of juvenile trevally, in response to different temperatures. Temperature conditions were experimentally manipulated for 1 month to mimic seasonal extremes. Phenotypic differences in growth were measured in 400 individuals, and the gene expression patterns of the pituitary gland and the liver were compared across treatments in a subset of 100 individuals, using RNA sequencing. Results showed that growth increased 50% more in the warmer compared with the colder condition, suggesting that temperature has a large impact on the metabolic activity associated with growth. We were able to annotate 27,887 gene models and found 39 differentially expressed genes (DEGs) in the pituitary, and 238 in the liver. Of these, 6 DEGs showed a common expression pattern between the tissues. Annotated blast matches of all DEGs revealed genes linked to major pathways affecting metabolism and reproduction. Our results indicate that native New Zealand trevally exhibit predictable plastic regulatory responses to temperature stress and the genes identified provide excellent for selective breeding objectives and studied how populations may adapt to increasing temperatures. Finally, Chapter 5 discusses the implications, future directions, and application of this research for trevally and other breeding programmes. It more broadly highlights the insights that were gained on the genetic architecture of growth, and the role of temperature in interacting and modulating genes involved in plastic growth responses.

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Detection and application of genome-wide variations in peach for association and genetic relationship analysis

BMC Genetics ◽

10.1186/s12863-019-0799-8 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 2

Author(s):

Liping Guan ◽

Ke Cao ◽

Yong Li ◽

Jian Guo ◽

Qiang Xu ◽

...

Keyword(s):

Genetic Relationship ◽

Dna Markers ◽

High Throughput Sequencing ◽

Prunus Persica ◽

Genetic Research ◽

Diploid Species ◽

Sequencing Data ◽

Relationship Analysis ◽

Genome Wide ◽

A Genome

Abstract Background Peach (Prunus persica L.) is a diploid species and model plant of the Rosaceae family. In the past decade, significant progress has been made in peach genetic research via DNA markers, but the number of these markers remains limited. Results In this study, we performed a genome-wide DNA markers detection based on sequencing data of six distantly related peach accessions. A total of 650,693~1,053,547 single nucleotide polymorphisms (SNPs), 114,227~178,968 small insertion/deletions (InDels), 8386~12,298 structure variants (SVs), 2111~2581 copy number variants (CNVs) and 229,357~346,940 simple sequence repeats (SSRs) were detected and annotated. To demonstrate the application of DNA markers, 944 SNPs were filtered for association study of fruit ripening time and 15 highly polymorphic SSRs were selected to analyze the genetic relationship among 221 accessions. Conclusions The results showed that the use of high-throughput sequencing to develop DNA markers is fast and effective. Comprehensive identification of DNA markers, including SVs and SSRs, would be of benefit to genetic diversity evaluation, genetic mapping, and molecular breeding of peach.

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Linkage mapping and genome-wide association reveal candidate genes conferring thermotolerance of seed-set in maize

Journal of Experimental Botany ◽

10.1093/jxb/erz171 ◽

2019 ◽

Vol 70 (18) ◽

pp. 4849-4864 ◽

Cited By ~ 8

Author(s):

Jingyang Gao ◽

Songfeng Wang ◽

Zijian Zhou ◽

Shiwei Wang ◽

Chaopei Dong ◽

...

Keyword(s):

Candidate Genes ◽

Linkage Mapping ◽

Genome Wide Association Study ◽

Seed Set ◽

Crop Yields ◽

Expression Profiles ◽

Snp Markers ◽

Genome Wide Association ◽

Genome Wide ◽

A Genome

AbstractIt is predicted that high-temperature stress will increasingly affect crop yields worldwide as a result of climate change. In order to determine the genetic basis of thermotolerance of seed-set in maize under field conditions, we performed mapping of quantitative trait loci (QTLs) in a recombinant inbred line (RIL) population using a collection of 8329 specifically developed high-density single-nucleotide polymorphism (SNP) markers, combined with a genome-wide association study (GWAS) of 261 diverse maize lines using 259 973 SNPs. In total, four QTLs and 17 genes associated with 42 SNPs related to thermotolerance of seed-set were identified. Among them, four candidate genes were found in both linkage mapping and GWAS. Thermotolerance of seed-set was increased significantly in near-isogenic lines (NILs) that incorporated the four candidate genes in a susceptible parent background. The expression profiles of two of the four genes showed that they were induced by high temperatures in the maize tassel in a tolerant parent background. Our results indicate that thermotolerance of maize seed-set is regulated by multiple genes each of which has minor effects, with calcium signaling playing a central role. The genes identified may be exploited in breeding programs to improve seed-set and yield of maize under heat stress.

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European landrace diversity for common bean biofortification: a genome-wide association study

Scientific Reports ◽

10.1038/s41598-020-76417-3 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Leonardo Caproni ◽

Lorenzo Raggi ◽

Elise F. Talsma ◽

Peter Wenzl ◽

Valeria Negri

Keyword(s):

Common Bean ◽

Genome Wide Association Study ◽

Preliminary Evidence ◽

Snp Markers ◽

Genome Wide Association ◽

Future Research ◽

Balanced Diet ◽

Genome Wide ◽

Seed Content ◽

A Genome

AbstractMineral deficiencies represent a global challenge that needs to be urgently addressed. An adequate intake of iron and zinc results in a balanced diet that reduces chances of impairment of many metabolic processes that can lead to clinical consequences. In plants, bioavailability of such nutrients is reduced by presence of compounds such as phytic acid, that can chelate minerals and reduce their absorption. Biofortification of common bean (Phaseolus vulgaris L.) represents an important strategy to reduce mineral deficiencies, especially in areas of the world where this crop plays a key role in the diet. In this study, a panel of diversity encompassing 192 homozygous genotypes, was screened for iron, zinc and phytate seed content. Results indicate a broad variation of these traits and allowed the identification of accessions reasonably carrying favourable trait combinations. A significant association between zinc seed content and some molecular SNP markers co-located on the common bean Pv01 chromosome was detected by means of genome-wide association analysis. The gene Phvul001G233500, encoding for an E3 ubiquitin-protein ligase, is proposed to explain detected associations. This result represents a preliminary evidence that can foster future research aiming at understanding the genetic mechanisms behind zinc accumulation in beans.

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