scholarly journals QTL Mapping for Grain Zinc and Iron Concentrations in Bread Wheat

2021 ◽  
Vol 8 ◽  
Author(s):  
Yue Wang ◽  
Xiaoting Xu ◽  
Yuanfeng Hao ◽  
Yelun Zhang ◽  
Yuping Liu ◽  
...  
Keyword(s):  
Recombinant Inbred Lines ◽  
Snp Array ◽  
Snp Markers ◽  
Environment Interaction ◽  
Single Nucleotide ◽  
Wide Range ◽  
Grain Zinc ◽  
Hidden Hunger ◽  
Range Of Variation ◽  
Selection Of

Deficiency of micronutrient elements, such as zinc (Zn) and iron (Fe), is called “hidden hunger,” and bio-fortification is the most effective way to overcome the problem. In this study, a high-density Affymetrix 50K single-nucleotide polymorphism (SNP) array was used to map quantitative trait loci (QTL) for grain Zn (GZn) and grain Fe (GFe) concentrations in 254 recombinant inbred lines (RILs) from a cross Jingdong 8/Bainong AK58 in nine environments. There was a wide range of variation in GZn and GFe concentrations among the RILs, with the largest effect contributed by the line × environment interaction, followed by line and environmental effects. The broad sense heritabilities of GZn and GFe were 0.36 ± 0.03 and 0.39 ± 0.03, respectively. Seven QTL for GZn on chromosomes 1DS, 2AS, 3BS, 4DS, 6AS, 6DL, and 7BL accounted for 2.2–25.1% of the phenotypic variances, and four QTL for GFe on chromosomes 3BL, 4DS, 6AS, and 7BL explained 2.3–30.4% of the phenotypic variances. QTL on chromosomes 4DS, 6AS, and 7BL might have pleiotropic effects on both GZn and GFe that were validated on a germplasm panel. Closely linked SNP markers were converted to high-throughput KASP markers, providing valuable tools for selection of improved Zn and Fe bio-fortification in breeding.

scholarly journals Clonal selection of Eucalyptus grandis x Eucalyptus globulus for productivity, adaptability, and stability, using SNP markers

2016 ◽  
Vol 65 (2) ◽  
pp. 30-38 ◽  
Author(s):  
D. Torres-Dini ◽  
A. C. P. Nunes ◽  
A. Aguiar ◽  
N. Nikichuk ◽  
C. Centurión ◽  
...  
Keyword(s):  
Eucalyptus Globulus ◽  
Environmental Changes ◽  
Clonal Selection ◽  
Eucalyptus Grandis ◽  
Small Population ◽  
Snp Markers ◽  
Hybrid Population ◽  
Environment Interaction ◽  
Predictive Capacity ◽  
Selection Of

Abstract In Uruguay, reforestations with Eucalyptus sp. is of fundamental importance to supply paper, pulp, and wood production. This study investigates genetic, productivity, stability, and adaptability parameters in the selection of Eucalypts grandis x Eucalyptus globulus full-sib hybrid clones. The study was conducted in a clonal test, repeated in two different soils types, in Rio Negro State, Uruguay. The population was characterized phenotypically for diameter at breast height (dbh) and genotyped for SNP markers (EuCHIP60K chip). Mean dbh was similar between sites and the genotype–environment interaction was simple. We found high genotype correlation in clone performance between environments (0.708), indicating the possibility of selecting the same clones for both study locations. Mean heritability between clones (0.724), coefficient of individual genetic variation (10.9 %), and relative variation (0.916), suggest the possibility of gains (estimated at 3.1 % for both sites together) by selecting clones with higher growth rates. A total of 15,196 SNPs were used to confirm parentage and test a genomic selection model for dbh. The predictive capacity was negative (-0.15) given the small population size (78 individuals). The most adaptable material among the tested study sites presented higher values for SNP heterozygosity. Thus, using molecular markers to identify clones responsive to environmental changes can act as a powerful tool in Eucalyptus breeding programs. The hybrid population showed greater adaptability than E. globulus for this region.

scholarly journals Mapping QTL for spike fertility related traits in two double haploid wheat (Triticum aestivum L.) populations

2020 ◽  
Author(s):  
Nicole Pretini ◽  
Leonardo S. Vanzetti ◽  
Ignacio I. Terrile ◽  
Guillermo Donaire ◽  
Fernanda G. González
Keyword(s):  
Double Haploid ◽  
Snp Array ◽  
Triticum Aestivum L ◽  
Yield Potential ◽  
Single Nucleotide ◽  
Breeding Programs ◽  
Grain Number Per Spike ◽  
Fertility Traits ◽  
Major Qtl ◽  
Selection Of

AbstractIn breeding programs, the selection of cultivars with the highest yield potential consisted in the selection of the yield per se, which resulted in cultivars with a higher grain number per spike (GN) and occasionally higher grain weight (GW) (main numerical components of the yield). This task could be facilitated with the use of molecular markers such us single nucleotide polymorphism (SNP). In this study, quantitative trait loci (QTL) for GW, GN and spike fertility traits related to GN determination were mapped using two double haploid (DH) populations (Baguette Premium 11 x BioINTA 2002 and Baguette 19 x BioINTA 2002, BP11xB2002 and B19xB2002). Both populations were genotyped with the iSelect 90K SNP array and evaluated in four (BP11xB19) or five (B19xB2002) environments. We identify a total of 305 QTL for 14 traits, however 28 QTL for 12 traits were considered significant with an R2 > 10% and stable for being present at least in three environments. There were detected eight hotspot regions on chromosomes 1A, 2B, 3A, 5A, 5B, 7A and 7B were at least two major QTL sheared confident intervals. QTL on two of these regions have previously been described, but the other six regions were never observed, suggesting that these regions would be novel. The R5A1 (QSL.perg-5A, QCN.perg-5A,QGN.perg-5A) and R5A.2 (QFFTS.perg-5A, QGW.perg-5A) regions together with the QGW.perg-6B resulted in a final higher yield suggesting them to have high relevance as candidates to be used in MAS to improve yield.Author contribution statementKey message28 stable and major QTL for 12 traits associated to spike fertility, GN and GW were detected. Two regions on 5A Ch., and QGW.perg-6B showed direct pleiotropic effects on yield.

Viability of Litchi chinensis seeds when stored in air and in water

1985 ◽  
Vol 104 (1) ◽  
pp. 247-248 ◽  
Author(s):  
P. K. Ray ◽  
S. B. Sharma
Keyword(s):  
Genetic Variability ◽  
Mangifera Indica ◽  
Litchi Chinensis ◽  
The Past ◽  
Wide Range ◽  
The World ◽  
Range Of Variation ◽  
Selection Of

India is the second largest litchi producing country in the world after China (Syamal & Mishra, 1984), yet the number of litchi cultivars grown in the country is quite small compared with mango (Mangifera indica). In mango most of the choicest Indian cultivars have been obtained from chance seedlings (Singh, 1960) grown in the past without any definite aim in mind. Litchi, as a result of crosspollination (Chaturvedi, 1965), is a highly heterozygous fruit, and as such, its seedlings, like those of mango, exhibit a wide range of variation which helps in the selection of new desired types. It has, thus, been emphasized that litchi should be grown in bulk from seeds to introduce genetic variability (Kumar & Thakur, 1981). Kadman & Slor (1974), encouraged by excellent success in grafting, have also stressed the need for raising plants through seeds for rootstocks.

scholarly journals Genetic diversity and association analysis of leafminer (Liriomyza langei) resistance in spinach (Spinacia oleracea)

Genome ◽  
2016 ◽  
Vol 59 (8) ◽  
pp. 581-588 ◽  
Author(s):  
Ainong Shi ◽  
Beiquan Mou
Keyword(s):  
Association Analysis ◽  
Spinacia Oleracea ◽  
Insect Pest ◽  
Genetic Resistance ◽  
Genotyping By Sequencing ◽  
Complex Trait ◽  
Snp Markers ◽  
Minor Effect ◽  
Single Nucleotide ◽  
Wide Range

Leafminer (Liriomyza langei) is a major insect pest of many important agricultural crops, including spinach (Spinacia oleracea). Use of genetic resistance is an efficient, economic, and environment-friendly method to control this pest. The objective of this research was to conduct association analysis and identify single nucleotide polymorphism (SNP) markers associated with leafminer resistance in spinach germplasm. A total of 300 USDA spinach germplasm accessions were used for the association analysis of leafminer resistance. Genotyping by sequencing (GBS) was used for genotyping and 783 SNPs from GBS were used for association analysis. The leafminer resistance showed a near normal distribution with a wide range from 1.1 to 11.7 stings per square centimeter leaf area, suggesting that the leafminer resistance in spinach is a complex trait controlled by multiple genes with minor effect in this spinach panel. Association analysis indicated that five SNP markers, AYZV02040968_7171, AYZV02076752_412, AYZV02098618_4615, AYZV02147304_383, and AYZV02271373_398, were associated with the leafminer resistance with LOD 2.5 or higher. The SNP markers may be useful for breeders to select plants and lines for leafminer resistance in spinach breeding programs through marker-assisted selection.

QTL mapping of early flowering and resistance to ascochyta blight in chickpea

Genome ◽  
2016 ◽  
Vol 59 (6) ◽  
pp. 413-425 ◽  
Author(s):  
Ketema Daba ◽  
Amit Deokar ◽  
Sabine Banniza ◽  
Thomas D. Warkentin ◽  
Bunyamin Tar’an
Keyword(s):  
Phenotypic Variation ◽  
Recombinant Inbred Lines ◽  
Ascochyta Blight ◽  
Snp Markers ◽  
Chromosome 8 ◽  
Flowering Plant ◽  
Blight Resistance ◽  
Days To Flowering ◽  
Growing Seasons ◽  
Wide Range

In western Canada, chickpea (Cicer arietinum L.) production is challenged by short growing seasons and infestations with ascochyta blight. Research was conducted to determine the genetic basis of the association between flowering time and reaction to ascochyta blight in chickpea. Ninety-two chickpea recombinant inbred lines (RILs) developed from a cross between ICCV 96029 and CDC Frontier were evaluated for flowering responses and ascochyta blight reactions in growth chambers and fields at multiple locations and during several years. A wide range of variation was exhibited by the RILs for days to flower, days to maturity, node of first flowering, plant height, and ascochyta blight resistance. Moderate to high broad sense heritability was estimated for ascochyta blight reaction (H2 = 0.14–0.34) and for days to flowering (H2 = 0.45–0.87) depending on the environments. Negative correlations were observed among the RILs for days to flowering and ascochyta blight resistance, ranging from r = −0.21 (P < 0.05) to −0.58 (P < 0.0001). A genetic linkage map consisting of eight linkage groups was developed using 349 SNP markers. Seven QTLs for days to flowering were identified that individually explained 9%–44% of the phenotypic variation. Eight QTLs were identified for ascochyta blight resistance that explained phenotypic variation ranging from 10% to 19%. Clusters of QTLs for days to flowering and ascochyta blight resistances were found on chromosome 3 at the interval of 8.6–23.11 cM and on chromosome 8 at the interval of 53.88–62.33 cM.

scholarly journals Effects of single nucleotide polymorphism ascertainment on population structure inferences

2021 ◽  
Author(s):  
Kotaro Dokan ◽  
Sayu Kawamura ◽  
Kosuke M Teshima
Keyword(s):  
Single Nucleotide Polymorphism ◽  
Population Structure ◽  
Natural Populations ◽  
Snp Markers ◽  
Ascertainment Bias ◽  
Snp Discovery ◽  
Nucleotide Polymorphism ◽  
Frequency Spectra ◽  
Single Nucleotide ◽  
Selection Of

Abstract Single nucleotide polymorphism (SNP) data are widely used in research on natural populations. Although they are useful, SNP genotyping data are known to contain bias, normally referred to as ascertainment bias, because they are conditioned by already confirmed variants. This bias is introduced during the genotyping process, including the selection of populations for novel SNP discovery and the number of individuals involved in the discovery panel and selection of SNP markers. It is widely recognized that ascertainment bias can cause inaccurate inferences in population genetics and several methods to address these bias issues have been proposed. However, especially in natural populations, it is not always possible to apply an ideal ascertainment scheme because natural populations tend to have complex structures and histories. In addition, it was not fully assessed if ascertainment bias has the same effect on different types of population structure. Here we examine the effects of bias produced during the selection of population for SNP discovery and consequent SNP marker selection processes under three demographic models: the island, stepping-stone, and population split models. Results show that site frequency spectra and summary statistics contain biases that depend on the joint effect of population structure and ascertainment schemes. Additionally, population structure inferences are also affected by ascertainment bias. Based on these results, it is recommended to evaluate the validity of the ascertainment strategy prior to the actual typing process because the direction and extent of ascertainment bias vary depending on several factors.

scholarly journals Impact of inclusion rates of crossbred phenotypes and genotypes in nucleus selection programs

2020 ◽  
Vol 98 (12) ◽  
Author(s):  
Garrett M See ◽  
Benny E Mote ◽  
Matthew L Spangler
Keyword(s):  
Data Collection ◽  
Genetic Correlation ◽  
Snp Markers ◽  
Breeding Value ◽  
Single Nucleotide ◽  
Data Collection Strategy ◽  
Inclusion Rate ◽  
Genetic Evaluations ◽  
The Impact ◽  
Selection Of

Abstract Numerous methods have been suggested to incorporate crossbred (CB) phenotypes and genotypes into swine selection programs, yet little research has focused on the implicit trade-off decisions between generating data at the nucleus or commercial level. The aim of this study was to investigate the impact of altering the proportion of purebred (PB) and CB phenotypes and genotypes in genetic evaluations on the response to selection of CB performance. Assuming CB and PB performance with moderate heritabilities (h2=0.4), a three-breed swine crossbreeding scheme was simulated and selection was practiced for six generations, where the goal was to increase CB performance. Phenotypes, genotypes, and pedigrees for three PB breeds (25 and 175 mating males and females for each breed, respectively), F1 crosses (400 mating females), and terminal cross progeny (2,500) were simulated. The genome consisted of 18 chromosomes with 1,800 quantitative trait loci and 72k single nucleotide polymorphism (SNP) markers. Selection was performed in PB breeds using estimated breeding value for each phenotyping/genotyping strategy. Strategies investigated were: 1) increasing the proportion of CB with genotypes, phenotypes, and sire pedigree relationships, 2) decreasing the proportion of PB phenotypes and genotypes, and 3) altering the genetic correlation between PB and CB performance (rpc). Each unique rpc scenario and data collection strategy was replicated 10 times. Results showed that including CB data improved the CB performance regardless of  rpc or data collection strategy compared with when no CB data were included. Compared with using only PB information, including 10% of CB progeny per generation with sire pedigrees and phenotypes increased the response in CB phenotype by 134%, 55%, 33%, 23%, and 21% when rpc was 0.1, 0.3, 0.5, 0.7, and 0.9, respectively. When the same 10% of CB progeny were also genotyped, CB performance increased by 243%, 54%, 38%, 23%, and 20% when the rpc was 0.1, 0.3, 0.5, 0.7, and 0.9, respectively, compared with when no CB data were utilized. Minimal change was observed in the average CB phenotype when PB phenotypes were included or proportionally removed when CB were genotyped. Removal of both PB phenotypes and genotypes when CB were genotyped greatly reduced the response in CB performance. In practice, the optimal inclusion rate of CB and PB data depends upon the genetic correlation between CB and PB animals and the expense of additional CB data collection compared with the economic benefit associated with increased CB performance.

scholarly journals Efficiency of using SNP markers in the MSTN gene in the selection of the Pushkin breed chickens

2020 ◽  
Vol 23 (8) ◽  
pp. 993-998 ◽  
Author(s):  
N. V. Dementeva ◽  
A. B. Vakhrameev ◽  
T. A. Larkina ◽  
O. V. Mitrofanova
Keyword(s):  
Molecular Genetic ◽  
Live Weight ◽  
Snp Markers ◽  
Experimental Population ◽  
Adult Bird ◽  
Nucleotide Polymorphisms ◽  
Poultry Industry ◽  
Single Nucleotide ◽  
Low Efficiency ◽  
Selection Of

In the poultry industry, indicators reflecting the growth rate of young stock and the exterior characteristics of chickens are important benchmarks for breeding. Traditional selection based on phenotypic evaluation is characterized by low efficiency with a low character inheritance ratio and is difficult to apply in small groups of animals and birds bred in bioresource collections. The use of molecular genetic markers associated with economically important traits makes it possible to carry out early selection of birds. This entails an increase in the profitability of the poultry industry. Recently, single nucleotide polymorphisms (SNPs) have served as convenient markers for selection purposes. For five generations (P1–P5), an experimental selection of hens of the Pushkin breed was carried out for live weight. It was based on selection for single nucleotide polymorphism rs313744840 in the MSTN gene. As a result, a significant increase in the frequency of allele A in this gene, from 0.11 to 0.50, took place. The association of SNP markers with meat qualities in the experimental group led to changes in the exterior profile of an adult bird at 330 days of age. The individuals with the AA and AG genotypes had the greatest live weight and longest body. As a result of selection, the bird on average became larger due to an increase in the number of heterozygous individuals with long bodies and large chest girths. The depth of the chest and the width of the pelvis increased due to an increase in the frequency of allele A in the experimental population. A tendency towards an increase in these indicators with the substitution of G with A in the genotype was found. Saturation of the population with desirable alleles led to an increase in the average live weight of the chickens. Analysis of the exterior parameters of adult birds showed that this growth is achieved by increasing the depth and volume of the bird body, and not by increasing the length of the limbs. Thus, marker selection carried out for five generations in the experimental population of Pushkin breed chickens to increase body weight has reliably (p < 0.001) changed the exterior profile of adult birds.

scholarly journals GWAS identifies a wheat orthologue of the rice D11 gene as an important contributor to grain size in an international collection of hexaploid wheat

2021 ◽  
Author(s):  
Honoré Tekeu ◽  
Eddy L.M. Ngonkeu ◽  
Sébastien Bélanger ◽  
Pierre F. Djocgoué ◽  
Amina Abed ◽  
...  
Keyword(s):  
Grain Size ◽  
Hexaploid Wheat ◽  
Snp Array ◽  
Genotyping By Sequencing ◽  
Snp Markers ◽  
Promising Candidate ◽  
Single Nucleotide ◽  
Grain Length ◽  
Snp Data ◽  
Genomic Regions

Abstract Grain size is a key agronomic trait that contributes to grain yield in hexaploid wheat. Grain length and width were evaluated in an international collection of 159 wheat accessions. These accessions were genetically characterized using a genotyping-by-sequencing (GBS) protocol that produced 73,784 single nucleotide polymorphism (SNP) markers. GBS-derived genotype calls obtained on Chinese Spring proved extremely accurate when compared to the reference (> 99.9%) and showed > 95% agreement with calls made at SNP loci shared with the 90K SNP array on a subset of 71 Canadian wheat accessions for which both types of data were available. This indicates that GBS can yield a large amount of highly accurate SNP data in hexaploid wheat. The genetic diversity analysis performed using this set of SNP markers revealed the presence of six distinct groups within this collection. A GWAS was conducted to uncover genomic regions controlling variation for grain length and width. In total, seven SNPs were found to be associated with one or both traits, identifying three quantitative trait loci (QTLs) located on chromosomes 1D, 2D and 4A. In the vicinity of the peak SNP on chromosome 2D, we found a promising candidate gene (TraesCS2D01G331100), whose rice ortholog (D11) had previously been reported to be involved in the regulation of grain size. These markers will be useful in breeding for enhanced wheat productivity.

scholarly journals GWAS identifies an ortholog of the rice D11 gene as a candidate gene for grain size in an international collection of hexaploid wheat

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Honoré Tekeu ◽  
Eddy L. M. Ngonkeu ◽  
Sébastien Bélanger ◽  
Pierre F. Djocgoué ◽  
Amina Abed ◽  
...  
Keyword(s):  
Grain Size ◽  
Candidate Gene ◽  
Hexaploid Wheat ◽  
Snp Array ◽  
Genotyping By Sequencing ◽  
Snp Markers ◽  
Single Nucleotide ◽  
Grain Length ◽  
Snp Data ◽  
Genomic Regions

AbstractGrain size is a key agronomic trait that contributes to grain yield in hexaploid wheat. Grain length and width were evaluated in an international collection of 157 wheat accessions. These accessions were genetically characterized using a genotyping-by-sequencing (GBS) protocol that produced 73,784 single nucleotide polymorphism (SNP) markers. GBS-derived genotype calls obtained on Chinese Spring proved extremely accurate when compared to the reference (> 99.9%) and showed > 95% agreement with calls made at SNP loci shared with the 90 K SNP array on a subset of 71 Canadian wheat accessions for which both types of data were available. This indicates that GBS can yield a large amount of highly accurate SNP data in hexaploid wheat. The genetic diversity analysis performed using this set of SNP markers revealed the presence of six distinct groups within this collection. A GWAS was conducted to uncover genomic regions controlling variation for grain length and width. In total, seven SNPs were found to be associated with one or both traits, identifying three quantitative trait loci (QTLs) located on chromosomes 1D, 2D and 4A. In the vicinity of the peak SNP on chromosome 2D, we found a promising candidate gene (TraesCS2D01G331100), whose rice ortholog (D11) had previously been reported to be involved in the regulation of grain size. These markers will be useful in breeding for enhanced wheat productivity.

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