scholarly journals Genome-wide association and prediction studies using a grapevine diversity panel give insights into the genetic architecture of several traits of interest

2020 ◽  
Author(s):  
T Flutre ◽  
L Le Cunff ◽  
A Fodor ◽  
A Launay ◽  
C Romieu ◽  
...  
Keyword(s):  
Yield Components ◽  
Prediction Accuracy ◽  
Genetic Architecture ◽  
Genetic Variance ◽  
Breeding Programs ◽  
Stress Indicator ◽  
Genome Wide ◽  
Aroma Precursors ◽  
Variance Explained ◽  
Response Variables

SummaryTo cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennials, but requires to understand the genetic architecture of important traits. To go beyond QTL mapping in bi-parental crosses, we exploited a diverse panel of 279 Vitis vinifera L. cultivars. This panel planted in five blocks in the vineyard was phenotyped over several years for 127 traits including yield components, organic acids, aroma precursors, polyphenols, and a water stress indicator. Such an experimental design allowed us to reliably assess the genotypic values for most traits. The panel was genotyped for 60k SNPs by combining an 18K microarray and sequencing (GBS). Marker densification via GBS markedly increased the proportion of genetic variance explained by SNPs, and two multi-SNP models identified QTLs not found by a SNP-by-SNP model. This led to 489 reliable QTLs using the combined microarray-GBS SNPs for 41% more response variables than a SNP-by-SNP model applied to microarray-only SNPs, and many QTLs were new compared to the results from bi-parental crosses. Prediction accuracy ranging from 0.14 to 0.84 for 80% of the response variables was promising for genomic selection, and provided insights into the genetic architecture of each trait when put in perspective with the number of QTLs and heritability.

scholarly journals Genetic architecture of nonadditive inheritance in Arabidopsis thaliana hybrids

2016 ◽  
Vol 113 (46) ◽  
pp. E7317-E7326 ◽  
Author(s):  
Danelle K. Seymour ◽  
Eunyoung Chae ◽  
Dominik G. Grimm ◽  
Carmen Martín Pizarro ◽  
Anette Habring-Müller ◽  
...  
Keyword(s):  
Arabidopsis Thaliana ◽  
Molecular Basis ◽  
Genetic Architecture ◽  
Genetic Basis ◽  
Genetic Variance ◽  
Candidate Region ◽  
Hybrid Vigor ◽  
Mads Box ◽  
Genome Wide ◽  
Half Diallel

The ubiquity of nonparental hybrid phenotypes, such as hybrid vigor and hybrid inferiority, has interested biologists for over a century and is of considerable agricultural importance. Although examples of both phenomena have been subject to intense investigation, no general model for the molecular basis of nonadditive genetic variance has emerged, and prediction of hybrid phenotypes from parental information continues to be a challenge. Here we explore the genetics of hybrid phenotype in 435 Arabidopsis thaliana individuals derived from intercrosses of 30 parents in a half diallel mating scheme. We find that nonadditive genetic effects are a major component of genetic variation in this population and that the genetic basis of hybrid phenotype can be mapped using genome-wide association (GWA) techniques. Significant loci together can explain as much as 20% of phenotypic variation in the surveyed population and include examples that have both classical dominant and overdominant effects. One candidate region inherited dominantly in the half diallel contains the gene for the MADS-box transcription factor AGAMOUS-LIKE 50 (AGL50), which we show directly to alter flowering time in the predicted manner. Our study not only illustrates the promise of GWA approaches to dissect the genetic architecture underpinning hybrid performance but also demonstrates the contribution of classical dominance to genetic variance.

scholarly journals The Genetic Architecture of Milling Quality in Spring Oat Lines of the Collaborative Oat Research Enterprise

Foods ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2479
Author(s):  
Kathy Esvelt Klos ◽  
Belayneh A. Yimer ◽  
Catherine J. Howarth ◽  
Michael S. McMullen ◽  
Mark E. Sorrells ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Human Consumption ◽  
Breeding Programs ◽  
Milling Quality ◽  
Milling Performance ◽  
Genome Wide ◽  
Trait Stability ◽  
Trait Variance ◽  
Mean And Variance ◽  
Pass Through

Most oat grains destined for human consumption must possess the ability to pass through an industrial de-hulling process with minimal breakage and waste. Uniform grain size and a high groat to hull ratio are desirable traits related to milling performance. The purpose of this study was to characterize the genetic architecture of traits related to milling quality by identifying quantitative trait loci (QTL) contributing to variation among a diverse collection of elite and foundational spring oat lines important to North American oat breeding programs. A total of 501 lines from the Collaborative Oat Research Enterprise (CORE) panel were evaluated for genome-wide association with 6 key milling traits. Traits were evaluated in 13 location years. Associations for 36,315 markers were evaluated for trait means across and within location years, as well as trait variance across location years, which was used to assess trait stability. Fifty-seven QTL influencing one or more of the milling quality related traits were identified, with fourteen QTL mapped influencing mean and variance across location years. The most prominent QTL was Qkernel.CORE.4D on chromosome 4D at approximately 212 cM, which influenced the mean levels of all traits. QTL were identified that influenced trait variance but not mean, trait mean only and both.

scholarly journals Genetic architecture of four smoking behaviors using partitioned h2SNP

2020 ◽  
Author(s):  
Luke M. Evans ◽  
Seonkyeong Jang ◽  
Marissa A. Ehringer ◽  
Jacqueline M. Otto ◽  
Scott I. Vrieze ◽  
...  
Keyword(s):  
Smoking Cessation ◽  
Genetic Architecture ◽  
Genetic Variance ◽  
Rare Variants ◽  
Low Frequency ◽  
Smoking Initiation ◽  
Uk Biobank ◽  
Genome Wide ◽  
Smoking Behaviors

AbstractBackground and AimsSmoking is a leading cause of premature death. Although genome-wide association studies have identified many loci that influence smoking behaviors, much of the genetic variance in these traits remains unexplained. We sought to characterize the genetic architecture of four smoking behaviors through SNP-based heritability (h2SNP) analyses.DesignWe applied recently-developed partitioned h2SNP approaches to smoking behavior traits assessed in the UK Biobank.SettingUK Biobank.ParticipantsUK Biobank participants of European ancestry. The number of participants varied depending on the trait, from 54,792 to 323,068.MeasurementsSmoking initiation, age of initiation, cigarettes per day (CPD; count, log-transformed, binned, and dichotomized into heavy versus light), and smoking cessation. Imputed genome-wide SNPs.FindingsWe estimated h2SNP(SE)=0.18(0.01) for smoking initiation and 0.12(0.02) for smoking cessation, which were more than twice the previously reported estimates. Estimated age of initiation h2SNP=0.05(0.01) and binned CPD h2SNP=0.1(0.01) were similar to previous reports. These estimates remained substantially below published twin-based h2 of roughly 50%. CPD encoding strongly influenced estimates, with dichotomized CPD h2SNP=0.28. We found significant contributions of low-frequency variants and variants in low linkage-disequilibrium (LD) with surrounding genomic regions. Functional annotations related to LD, allele frequency, sequence conservation, and selective constraint also contributed significantly to the partitioned heritability. We found no evidence of dominance genetic variance for any trait.Conclusionh2SNP of these four specific smoking behaviors is modest overall. The patterns of partitioned h2SNP for these highly polygenic traits is consistent with negative selection. We found a predominant contribution of common variants, and our results suggest a role of low-frequency or rare variants, poorly tagged by surrounding regions. Deep sequencing of large samples and/or improved imputation will be required to fully assess the role of rare variants.

Identification of new semen trait-related candidate genes in Duroc boars through genome-wide association and weighted gene co-expression network analyses

2021 ◽  
Author(s):  
Quanshun Mei ◽  
Chuanke Fu ◽  
Goutam Sahana ◽  
Yilong Chen ◽  
Lilin Yin ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Genetic Architecture ◽  
Genetic Variance ◽  
Sperm Concentration ◽  
Genome Wide Association ◽  
Pig Production ◽  
Network Analyses ◽  
Genetic Region ◽  
Genome Wide ◽  
A Genome

Abstract Semen traits are crucial in commercial pig production since semen from boars is widely used in artificial insemination for both purebred and crossbred pig production. Revealing the genetic architecture of semen traits potentially promotes the efficiencies of improving semen traits through artificial selection. This study is aimed to identify candidate genes related to the semen traits in Duroc boars. First, we identified the genes that were significantly associated with three semen traits, including sperm motility (MO), sperm concentration (CON), and semen volume (VOL) in a Duroc boar population through a genome wide association study (GWAS). Second, we performed a weighted gene co-expression network analysis (WGCNA). A total of 2, 3, and 20 SNPs were found to be significantly associated with MO, CON, and VOL, respectively. Based on the haplotype block analysis, we identified one genetic region associated with MO, which explained 6.15% of the genetic trait variance. ENSSSCG00000018823 located within this region was considered as the candidate gene for regulating MO. Another genetic region explaining 1.95% of CON genetic variance was identified, and in this region B9D2, PAFAH1B3, TMEM145, and CIC were detected as the CON-related candidate genes. Two genetic regions that accounted for 2.23% and 2.48% of VOL genetic variance were identified, and in these two regions, WWC2, CDKN2AIP, ING2, TRAPPC11, STOX2, and PELO were identified as VOL-related candidate genes. WGCNA analysis showed that among these candidate genes, B9D2, TMEM145, WWC2, CDKN2AIP, TRAPPC11, and PELO were located within the most significant module eigengenes, confirming these candidate genes’ role in regulating semen traits in Duroc boars. The identification of these candidate genes can help to better understand the genetic architecture of semen traits in boars. Our findings can be applied for semen traits improvement in Duroc boars.

scholarly journals Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing among full-sibs

2021 ◽  
Author(s):  
Antoine Fraimout ◽  
Zitong Li ◽  
Mikko J. Sillanpää ◽  
Pasi Rastas ◽  
Juha Merilä
Keyword(s):  
Natural Selection ◽  
Variance Components ◽  
Genetic Architecture ◽  
Quantitative Traits ◽  
Genetic Parameters ◽  
Genetic Variance ◽  
Identity By Descent ◽  
Quantitative Genetic ◽  
Genome Wide ◽  
Quantitative Genetic Parameters

ABSTRACTAdditive and dominance genetic variances underlying the expression of quantitative traits are important quantities for predicting short-term responses to selection, but they are notoriously challenging to estimate in most wild animal populations. Using estimates of genome-wide identity-by-descent (IBD) sharing from autosomal SNP loci, we estimated quantitative genetic parameters for traits known to be under directional natural selection in nine-spined sticklebacks (Pungitius pungitius) and compared these to traditional pedigree-based estimators. Using four different datasets, with varying sample sizes and pedigree complexity, we further assessed the performance of different Genomic Relationship Matrices (GRM) to estimate additive and dominance variance components. Large variance in IBD relationships allowed accurate estimation of genetic variance components, and revealed significant heritability for all measured traits, with negligible dominance contributions. Genome-partitioning analyses revealed that all traits have a polygenic basis and are controlled by genes at multiple chromosomes. The results demonstrate how large full-sib families of highly fecund vertebrates can be used to obtain accurate estimates quantitative genetic parameters to provide insights on genetic architecture of quantitative traits in non-model organisms from the wild. This approach should be particularly useful for studies requiring estimates of genetic variance components from multiple populations as for instance when aiming to infer the role of natural selection as a cause for population differentiation in quantitative traits.

scholarly journals Genome-wide association analysis uncovers the genetic architecture of tradeoff between flowering date and yield components in sesame

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Idan Sabag ◽  
Gota Morota ◽  
Zvi Peleg
Keyword(s):  
Phenotypic Variation ◽  
Yield Components ◽  
Genetic Architecture ◽  
Agronomic Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Flowering Date ◽  
Genome Wide ◽  
The Mediterranean

Abstract Background Unrevealing the genetic makeup of crop morpho-agronomic traits is essential for improving yield quality and sustainability. Sesame (Sesamum indicum L.) is one of the oldest oil-crops in the world. Despite its economic and agricultural importance, it is an ‘orphan crop-plant’ that has undergone limited modern selection, and, as a consequence preserved wide genetic diversity. Here we established a new sesame panel (SCHUJI) that contains 184 genotypes representing wide phenotypic variation and is geographically distributed. We harnessed the natural variation of this panel to perform genome-wide association studies for morpho-agronomic traits under the Mediterranean climate conditions. Results Field-based phenotyping of the SCHUJI panel across two seasons exposed wide phenotypic variation for all traits. Using 20,294 single-nucleotide polymorphism markers, we detected 50 genomic signals associated with these traits. Major genomic region on LG2 was associated with flowering date and yield-related traits, exemplified the key role of the flowering date on productivity. Conclusions Our results shed light on the genetic architecture of flowering date and its interaction with yield components in sesame and may serve as a basis for future sesame breeding programs in the Mediterranean basin.

scholarly journals Genome-wide association uncovers the genetic architecture of tradeoff between flowering date and yield components in sesame

2021 ◽  
Author(s):  
Idan Sabag ◽  
Gota Morota ◽  
Zvi Peleg
Keyword(s):  
Yield Components ◽  
Genetic Architecture ◽  
Agronomic Traits ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Climate Conditions ◽  
Flowering Date ◽  
Genome Wide ◽  
The Mediterranean

AbstractUnrevealing the genetic makeup of crop morpho-agronomic traits is essential for improving yield quality and sustainability. Sesame (Sesamum indicum L.), one of the oldest oil-crops in the world, which despite its economical and agricultural importance, is an ‘orphan crop-plant’ that undergone limited modern selection, thus, preserving wide genetic diversity. Here we harnessed this natural variation in a newly developed sesame panel (SCHUJI) to perform genome-wide association studies for morpho-agronomic traits under the Mediterranean climate conditions. Field-based phenotyping of the SCHUJI panel across two seasons exposed wide phenotypic variation for all traits. Using 20,294 single-nucleotide polymorphism markers, we detected 50 genomic signals associated with these traits. Major genomic region on LG2 was associated with flowering date and yield-related traits, exemplified the key role of the flowering date on productivity. Our results shed light on the genetic architecture of flowering date and its interaction with yield components in sesame and may serve as a basis for future sesame breeding programs in the Mediterranean basin.

scholarly journals A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth And Development ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Average Daily Gain ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

scholarly journals Genetic variability and genome-wide association analysis of flavor and texture in cooked beans (Phaseolus vulgaris L.)

2021 ◽  
Author(s):  
Amber Bassett ◽  
Kelvin Kamfwa ◽  
Daniel Ambachew ◽  
Karen Cichy
Keyword(s):  
Genetic Variability ◽  
Seed Coat ◽  
Principal Component ◽  
Breeding Programs ◽  
Flavor Intensity ◽  
Genome Wide ◽  
White Bean ◽  
The Usa ◽  
New Varieties ◽  
End Use

Abstract Key message Cooked bean flavor and texture vary within and across 20 Andean seed types; SNPs are significantly associated with total flavor, beany, earthy, starchy, bitter, seed-coat perception, and cotyledon texture. Abstract Common dry beans are a nutritious food recognized as a staple globally, but their consumption is low in the USA. Improving bean flavor and texture through breeding has the potential to improve consumer acceptance and suitability for new end-use products. Little is known about genetic variability and inheritance of bean sensory characteristics. A total of 430 genotypes of the Andean Diversity Panel representing twenty seed types were grown in three locations, and cooked seeds were evaluated by a trained sensory panel for flavor and texture attribute intensities, including total flavor, beany, vegetative, earthy, starchy, sweet, bitter, seed-coat perception, and cotyledon texture. Extensive variation in sensory attributes was found across and within seed types. A set of genotypes was identified that exhibit extreme attribute intensities generally stable across all three environments. seed-coat perception and total flavor intensity had the highest broad-sense heritability (0.39 and 0.38, respectively), while earthy and vegetative intensities exhibited the lowest (0.14 and 0.15, respectively). Starchy and sweet flavors were positively correlated and highest in white bean genotypes according to principal component analysis. SNPs associated with total flavor intensity (six SNPs across three chromosomes), beany (five SNPs across four chromosomes), earthy (three SNPs across two chromosomes), starchy (one SNP), bitter (one SNP), seed-coat perception (three SNPs across two chromosomes), and cotyledon texture (two SNPs across two chromosomes) were detected. These findings lay a foundation for incorporating flavor and texture in breeding programs for the development of new varieties that entice growers, consumers, and product developers alike.

scholarly journals Genetic architecture underlying the expression of eight α-amylase trypsin inhibitors

2021 ◽  
Author(s):  
Khaoula EL Hassouni ◽  
Malte Sielaff ◽  
Valentina Curella ◽  
Manjusha Neerukonda ◽  
Willmar Leiser ◽  
...  
Keyword(s):  
Genetic Architecture ◽  
Intestinal Inflammation ◽  
Wheat Breeding ◽  
Trypsin Inhibitors ◽  
Potential Candidate ◽  
Lipid Transfer ◽  
Wheat Cultivars ◽  
Genome Wide ◽  
Close Physical Proximity ◽  
Major Qtl

Abstract Key message Wheat cultivars largely differ in the content and composition of ATI proteins, but heritability was quite low for six out of eight ATIs. The genetic architecture of ATI proteins is built up of few major and numerous small effect QTL. Abstract Amylase trypsin inhibitors (ATIs) are important allergens in baker’s asthma and suspected triggers of non-celiac wheat sensitivity (NCWS) inducing intestinal and extra-intestinal inflammation. As studies on the expression and genetic architecture of ATI proteins in wheat are lacking, we evaluated 149 European old and modern bread wheat cultivars grown at three different field locations for their content of eight ATI proteins. Large differences in the content and composition of ATIs in the different cultivars were identified ranging from 3.76 pmol for ATI CM2 to 80.4 pmol for ATI 0.19, with up to 2.5-fold variation in CM-type and up to sixfold variation in mono/dimeric ATIs. Generally, heritability estimates were low except for ATI 0.28 and ATI CM2. ATI protein content showed a low correlation with quality traits commonly analyzed in wheat breeding. Similarly, no trends were found regarding ATI content in wheat cultivars originating from numerous countries and decades of breeding history. Genome-wide association mapping revealed a complex genetic architecture built of many small, few medium and two major quantitative trait loci (QTL). The major QTL were located on chromosomes 3B for ATI 0.19-like and 6B for ATI 0.28, explaining 70.6 and 68.7% of the genotypic variance, respectively. Within close physical proximity to the medium and major QTL, we identified eight potential candidate genes on the wheat reference genome encoding structurally related lipid transfer proteins. Consequently, selection and breeding of wheat cultivars with low ATI protein amounts appear difficult requiring other strategies to reduce ATI content in wheat products.

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