ResearchPad - quantitative-trait-loci https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Genome-wide association study of partial resistance to sclerotinia stem rot of cultivated soybean based on the detached leaf method]]> https://www.researchpad.co/article/elastic_article_15721 Sclerotinia stem rot (SSR) is a devastating fungal disease that causes severe yield losses of soybean worldwide. In the present study, a representative population of 185 soybean accessions was selected and utilized to identify the quantitative trait nucleotide (QTN) of partial resistance to soybean SSR via a genome-wide association study (GWAS). A total of 22,048 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAF) > 5% and missing data < 3% were used to assess linkage disequilibrium (LD) levels. Association signals associated with SSR partial resistance were identified by two models, including compressed mixed linear model (CMLM) and multi-locus random-SNP-effect mixed linear model (mrMLM). Finally, seven QTNs with major effects (a known locus and six novel loci) via CMLM and nine novel QTNs with minor effects via mrMLM were detected in relation to partial resistance to SSR, respectively. One of all the novel loci (Gm05:14834789 on Chr.05), which was co-located by these two methods, might be a stable one that showed high significance in SSR partial resistance. Additionally, a total of 71 major and 85 minor candidate genes located in the 200-kb genomic region of each peak SNP detected by CMLM and mrMLM were found, respectively. By using a gene-based association, a total of six SNPs from three major effects genes and eight SNPs from four minor effects genes were identified. Of them, Glyma.18G012200 has been characterized as a significant element in controlling fungal disease in plants.

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<![CDATA[An improved 7K SNP array, the C7AIR, provides a wealth of validated SNP markers for rice breeding and genetics studies]]> https://www.researchpad.co/article/elastic_article_14581 Single nucleotide polymorphisms (SNPs) are highly abundant, amendable to high-throughput genotyping, and useful for a number of breeding and genetics applications in crops. SNP frequencies vary depending on the species and populations under study, and therefore target SNPs need to be carefully selected to be informative for each application. While multiple SNP genotyping systems are available for rice (Oryza sativa L. and its relatives), they vary in their informativeness, cost, marker density, speed, flexibility, and data quality. In this study, we report the development and performance of the Cornell-IR LD Rice Array (C7AIR), a second-generation SNP array containing 7,098 markers that improves upon the previously released C6AIR. The C7AIR is designed to detect genome-wide polymorphisms within and between subpopulations of O. sativa, as well as O. glaberrima, O. rufipogon and O. nivara. The C7AIR combines top-performing SNPs from several previous rice arrays, including 4,007 SNPs from the C6AIR, 2,056 SNPs from the High Density Rice Array (HDRA), 910 SNPs from the 384-SNP GoldenGate sets, 189 SNPs from the 44K array selected to add information content for elite U.S. tropical japonica rice varieties, and 8 trait-specific SNPs. To demonstrate its utility, we carried out a genome-wide association analysis for plant height, employing the C7AIR across a diversity panel of 189 rice accessions and identified 20 QTLs contributing to plant height. The C7AIR SNP chip has so far been used for genotyping >10,000 rice samples. It successfully differentiates the five subpopulations of Oryza sativa, identifies introgressions from wild and exotic relatives, and is useful for quantitative trait loci (QTL) and association mapping in diverse materials. Moreover, data from the C7AIR provides valuable information that can be used to select informative and reliable SNP markers for conversion to lower-cost genotyping platforms for genomic selection and other downstream applications in breeding.

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<![CDATA[Comparison of infinitesimal and finite locus models for long-term breeding simulations with direct and maternal effects at the example of honeybees]]> https://www.researchpad.co/article/5c897737d5eed0c4847d272e

Stochastic simulation studies of animal breeding have mostly relied on either the infinitesimal genetic model or finite polygenic models. In this study, we investigated the long-term effects of the chosen model on honeybee breeding schemes. We implemented the infinitesimal model, as well as finite locus models, with 200 and 400 gene loci and simulated populations of 300 and 1000 colonies per year over the course of 100 years. The selection was of a directly and maternally influenced trait with maternal heritability of hm2=0.42, direct heritability of hd2=0.27, and a negative correlation between the effects of rmd = − 0.18. Another set of simulations was run with parameters hm2=0.53, hd2=0.34, and rmd = − 0.53. All models showed similar behavior for the first 20 years. Throughout the study, we observed a higher genetic gain in the direct than in the maternal effects and a smaller gain with a stronger negative covariance. In the long-term, however, only the infinitesimal model predicted sustainable linear genetic progress, while the finite locus models showed sublinear behavior and, after 100 years, only reached between 58% and 62% of the mean breeding values in the infinitesimal model. While the infinitesimal model suggested a reduction of genetic variance by 33% to 49% after 100 years, the finite locus models saw a more drastic loss of 76% to 92%. When designing sustainable breeding strategies, one should, therefore, not blindly trust the infinitesimal model as the predictions may be overly optimistic. Instead, the more conservative choice of the finite locus model should be favored.

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<![CDATA[Genome-wide haplotype-based association analysis of key traits of plant lodging and architecture of maize identifies major determinants for leaf angle: hapLA4]]> https://www.researchpad.co/article/5c89773ed5eed0c4847d27e7

Traits related to plant lodging and architecture are important determinants of plant productivity in intensive maize cultivation systems. Motivated by the identification of genomic associations with the leaf angle, plant height (PH), ear height (EH) and the EH/PH ratio, we characterized approximately 7,800 haplotypes from a set of high-quality single nucleotide polymorphisms (SNPs), in an association panel consisting of tropical maize inbred lines. The proportion of the phenotypic variations explained by the individual SNPs varied between 7%, for the SNP S1_285330124 (located on chromosome 9 and associated with the EH/PH ratio), and 22%, for the SNP S1_317085830 (located on chromosome 6 and associated with the leaf angle). A total of 40 haplotype blocks were significantly associated with the traits of interest, explaining up to 29% of the phenotypic variation for the leaf angle, corresponding to the haplotype hapLA4.04, which was stable over two growing seasons. Overall, the associations for PH, EH and the EH/PH ratio were environment-specific, which was confirmed by performing a model comparison analysis using the information criteria of Akaike and Schwarz. In addition, five stable haplotypes (83%) and 15 SNPs (75%) were identified for the leaf angle. Finally, approximately 62% of the associated haplotypes (25/40) did not contain SNPs detected in the association study using individual SNP markers. This result confirms the advantage of haplotype-based genome-wide association studies for examining genomic regions that control the determining traits for architecture and lodging in maize plants.

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<![CDATA[Analysis of genetic control and QTL mapping of essential wheat grain quality traits in a recombinant inbred population]]> https://www.researchpad.co/article/5c897730d5eed0c4847d2663

Wheat cultivars are genetically crossed to improve end-use quality for traits as per demands of baking industry and broad consumer preferences. The processing and baking qualities of bread wheat are influenced by a variety of genetic make-ups, environmental factors and their interactions. Two wheat cultivars, WL711 and C306, derived recombinant inbred lines (RILs) with a population of 206, were used for phenotyping of quality-related traits. The genetic analysis of quality traits showed considerable variation for measurable quality traits, with normal distribution and transgressive segregation across the years. From the 206 RILs, few RILs were found to be superior to those of the parental cultivars for key quality traits, indicating their potential use for the improvement of end-use quality and suggesting the probability of finding new alleles and allelic combinations from the RIL population. Mapping analysis identified 38 putative QTLs for 13 quality-related traits, with QTLs explaining 7.9–16.8% phenotypic variation spanning over 14 chromosomes, i.e., 1A, 1B, 1D, 2A, 2D, 3B, 3D, 4A, 4B, 4D, 5D, 6A, 7A and 7B. In-silico analysis based on homology to the annotated wheat genes present in database, identified six putative candidate genes within QTL for total grain protein content, qGPC.1B.1 region. Major QTL regions for other quality traits such as TKW have been identified on 1B, 2A, and 7A chromosomes in the studied RIL population. This study revealed the importance of the combination of stable QTLs with region-specific QTLs for better phenotyping, and the QTLs presented in our study will be useful for the improvement of wheat grain and bread-making quality.

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<![CDATA[A novel resistance gene for bacterial blight in rice, Xa43(t) identified by GWAS, confirmed by QTL mapping using a bi-parental population]]> https://www.researchpad.co/article/5c6c75dbd5eed0c4843d0337

Bacterial blight (BB) caused by the Xanthomonas oryzae pv. oryzae (Xoo) pathogen is a significant disease in most rice cultivation areas. The disease is estimated to cause annual rice production losses of 20–30 percent throughout rice-growing countries in Asia. The discovery and deployment of durable resistance genes for BB is an effective and sustainable means of mitigating production losses. In this study QTL analysis and fine mapping were performed using an F2 and a BC2F2 population derived from a cross with a new R-donor having broad spectrum resistance to Korean BB races. The QTL qBB11 was identified by composite interval mapping and explained 31.25% of the phenotypic variation (R2) with LOD values of 43.44 harboring two SNP markers. The single major R-gene was designated Xa43 (t). Through dissection of the target region we were able to narrow the region to within 27.83–27.95 Mbp, a physical interval of about 119-kb designated by the two flanking markers IBb27os11_14 and S_BB11.ssr_9. Of nine ORFs in the target region two ORFs revealed significantly different expression levels of the candidate genes. From these results we developed a marker specific to this R-gene, which will have utility for future BB resistance breeding and/or R-gene pyramiding using marker assisted selection. Further characterization of the R-gene would be helpful to enhance understanding of mechanisms of BB resistance in rice.

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<![CDATA[Variance components for bovine tuberculosis infection and multi-breed genome-wide association analysis using imputed whole genome sequence data]]> https://www.researchpad.co/article/5c6f1539d5eed0c48467af0c

Bovine tuberculosis (bTB) is an infectious disease of cattle generally caused by Mycobacterium bovis, a bacterium that can elicit disease humans. Since the 1950s, the objective of the national bTB eradication program in Republic of Ireland was the biological extinction of bTB; that purpose has yet to be achieved. Objectives of the present study were to develop the statistical methodology and variance components to undertake routine genetic evaluations for resistance to bTB; also of interest was the detection of regions of the bovine genome putatively associated with bTB infection in dairy and beef breeds. The novelty of the present study, in terms of research on bTB infection, was the use of beef breeds in the genome-wide association and the utilization of imputed whole genome sequence data. Phenotypic bTB data on 781,270 animals together with imputed whole genome sequence data on 7,346 of these animals’ sires were available. Linear mixed models were used to quantify variance components for bTB and EBVs were validated. Within-breed and multi-breed genome-wide associations were undertaken using a single-SNP regression approach. The estimated genetic standard deviation (0.09), heritability (0.12), and repeatability (0.30) substantiate that genetic selection help to eradicate bTB. The multi-breed genome-wide association analysis identified 38 SNPs and 64 QTL regions associated with bTB infection; two QTL regions (both on BTA23) identified in the multi-breed analysis overlapped with the within-breed analyses of Charolais, Limousin, and Holstein-Friesian. Results from the association analysis, coupled with previous studies, suggest bTB is controlled by an infinitely large number of loci, each having a small effect. The methodology and results from the present study will be used to develop national genetic evaluations for bTB in the Republic of Ireland. In addition, results can also be used to help uncover the biological architecture underlying resistance to bTB infection in cattle.

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<![CDATA[Training set optimization of genomic prediction by means of EthAcc]]> https://www.researchpad.co/article/5c75ac8dd5eed0c484d08a24

Genomic prediction is a useful tool for plant and animal breeding programs and is starting to be used to predict human diseases as well. A shortcoming that slows down the genomic selection deployment is that the accuracy of the prediction is not known a priori. We propose EthAcc (Estimated THeoretical ACCuracy) as a method for estimating the accuracy given a training set that is genotyped and phenotyped. EthAcc is based on a causal quantitative trait loci model estimated by a genome-wide association study. This estimated causal model is crucial; therefore, we compared different methods to find the one yielding the best EthAcc. The multilocus mixed model was found to perform the best. We compared EthAcc to accuracy estimators that can be derived via a mixed marker model. We showed that EthAcc is the only approach to correctly estimate the accuracy. Moreover, in case of a structured population, in accordance with the achieved accuracy, EthAcc showed that the biggest training set is not always better than a smaller and closer training set. We then performed training set optimization with EthAcc and compared it to CDmean. EthAcc outperformed CDmean on real datasets from sugar beet, maize, and wheat. Nonetheless, its performance was mainly due to the use of an optimal but inaccessible set as a start of the optimization algorithm. EthAcc’s precision and algorithm issues prevent it from reaching a good training set with a random start. Despite this drawback, we demonstrated that a substantial gain in accuracy can be obtained by performing training set optimization.

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<![CDATA[Genetic dissection of assortative mating behavior]]> https://www.researchpad.co/article/5c65dcb4d5eed0c484dec08b

The evolution of new species is made easier when traits under divergent ecological selection are also mating cues. Such ecological mating cues are now considered more common than previously thought, but we still know little about the genetic changes underlying their evolution or more generally about the genetic basis for assortative mating behaviors. Both tight physical linkage and the existence of large-effect preference loci will strengthen genetic associations between behavioral and ecological barriers, promoting the evolution of assortative mating. The warning patterns of Heliconius melpomene and H. cydno are under disruptive selection due to increased predation of nonmimetic hybrids and are used during mate recognition. We carried out a genome-wide quantitative trait locus (QTL) analysis of preference behaviors between these species and showed that divergent male preference has a simple genetic basis. We identify three QTLs that together explain a large proportion (approximately 60%) of the difference in preference behavior observed between the parental species. One of these QTLs is just 1.2 (0–4.8) centiMorgans (cM) from the major color pattern gene optix, and, individually, all three have a large effect on the preference phenotype. Genomic divergence between H. cydno and H. melpomene is high but broadly heterogenous, and admixture is reduced at the preference–optix color pattern locus but not the other preference QTLs. The simple genetic architecture we reveal will facilitate the evolution and maintenance of new species despite ongoing gene flow by coupling behavioral and ecological aspects of reproductive isolation.

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<![CDATA[Environment-dependent pleiotropic effects of mutations on the maximum growth rate r and carrying capacity K of population growth]]> https://www.researchpad.co/article/5c57e656d5eed0c484ef2c2a

Maximum growth rate per individual (r) and carrying capacity (K) are key life-history traits that together characterize the density-dependent population growth and therefore are crucial parameters of many ecological and evolutionary theories such as r/K selection. Although r and K are generally thought to correlate inversely, both r/K tradeoffs and trade-ups have been observed. Nonetheless, neither the conditions under which each of these relationships occur nor the causes of these relationships are fully understood. Here, we address these questions using yeast as a model system. We estimated r and K using the growth curves of over 7,000 yeast recombinants in nine environments and found that the rK correlation among genotypes changes from 0.53 to −0.52 with the rise of environment quality, measured by the mean r of all genotypes in the environment. We respectively mapped quantitative trait loci (QTLs) for r and K in each environment. Many QTLs simultaneously influence r and K, but the directions of their effects are environment dependent such that QTLs tend to show concordant effects on the two traits in poor environments but antagonistic effects in rich environments. We propose that these contrasting trends are generated by the relative impacts of two factors—the tradeoff between the speed and efficiency of ATP production and the energetic cost of cell maintenance relative to reproduction—and demonstrate an agreement between model predictions and empirical observations. These results reveal and explain the complex environment dependency of the rK relationship, which bears on many ecological and evolutionary phenomena and has biomedical implications.

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<![CDATA[Genome-wide association mapping of grain yield in a diverse collection of spring wheat (Triticum aestivum L.) evaluated in southern Australia]]> https://www.researchpad.co/article/5c61e8c8d5eed0c48496f180

Wheat landraces, wild relatives and other ‘exotic’ accessions are important sources of new favorable alleles. The use of those exotic alleles is facilitated by having access to information on the association of specific genomic regions with desirable traits. Here, we conducted a genome-wide association study (GWAS) using a wheat panel that includes landraces, synthetic hexaploids and other exotic wheat accessions to identify loci that contribute to increases in grain yield in southern Australia. The 568 accessions were grown in the field during the 2014 and 2015 seasons and measured for plant height, maturity, spike length, spike number, grain yield, plant biomass, HI and TGW. We used the 90K SNP array and two GWAS approaches (GAPIT and QTCAT) to identify loci associated with the different traits. We identified 17 loci with GAPIT and 25 with QTCAT. Ten of these loci were associated with known genes that are routinely employed in marker assisted selection such as Ppd-D1 for maturity and Rht-D1 for plant height and seven of those were detected with both methods. We identified one locus for yield per se in 2014 on chromosome 6B with QTCAT and three in 2015, on chromosomes 4B and 5A with GAPIT and 6B with QTCAT. The 6B loci corresponded to the same region in both years. The favorable haplotypes for yield at the 5A and 6B loci are widespread in Australian accessions with 112 out of 153 carrying the favorable haplotype at the 5A locus and 136 out of 146 carrying the favorable haplotype at the 6A locus, while the favorable haplotype at 4B is only present in 65 out of 149 Australian accessions. The low number of yield QTL in our study corroborate with other GWAS for yield in wheat, where most of the identified loci have very small effects.

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<![CDATA[Genetics of zonal leaf chlorosis and genetic linkage to a major gene regulating skin anthocyanin production (MdMYB1) in the apple (Malus × domestica) cultivar Honeycrisp]]> https://www.researchpad.co/article/5c58d667d5eed0c484031d98

‘Honeycrisp’ is a widely grown and acclaimed apple cultivar that is commonly used in breeding programs. It also has a well-documented tendency to develop the physiological disorder, zonal leaf chlorosis (ZLC). This disorder causes reduced photosynthetic capacity and is thought to be due to a problem with phloem loading, although the underlying genetics of the disorder have not previously been discerned. In order to understand the breeding implications of the disorder, six families with ‘Honeycrisp’ as a parent and one family with ‘Honeycrisp’ as both a maternal and paternal grandparent were evaluated for ZLC incidence over two years. One major quantitative trait locus (QTL) for ZLC incidence was identified on linkage group (LG) 9. A haplotype in ‘Honeycrisp’ that originated from grandparent ‘Duchess of Oldenburg’ was associated with increased ZLC incidence in offspring in both years and all families evaluated. The LG9 QTL was 5 to 10 cM from MdMYB1, which is a major gene regulating fruit skin anthocyanin production. ‘Honeycrisp’ is heterozygous for red fruit skin overcolor at MdMYB1. The ‘Honeycrisp’ haplotype at the LG9 QTL associated with increased ZLC is in linkage phase with the allele at MdMYB1 associated with red color. Selection for the red allele from ‘Honeycrisp’ at MdMYB1 will result in most offspring also inheriting the haplotype at the LG9 QTL associated with high ZLC. The occurrence of two copies of this haplotype was sub-lethal in seedlings of a family where both parents inherited both the red overcolor allele at MdMYB1 and the haplotype at the LG9 QTL associated with high ZLC. This is the first study to have identified a genetic component of ZLC with clear breeding implications.

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<![CDATA[Criteria for evaluating molecular markers: Comprehensive quality metrics to improve marker-assisted selection]]> https://www.researchpad.co/article/5c478c38d5eed0c484bd0df6

Despite strong interest over many years, the usage of quantitative trait loci in plant breeding has often failed to live up to expectations. A key weak point in the utilisation of QTLs is the “quality” of markers used during marker-assisted selection (MAS): unreliable markers result in variable outcomes, leading to a perception that MAS products fail to achieve reliable improvement. Most reports of markers used for MAS focus on markers derived from the mapping population. There are very few studies that examine the reliability of these markers in other genetic backgrounds, and critically, no metrics exist to describe and quantify this reliability. To improve the MAS process, this work proposes five core metrics that fully describe the reliability of a marker. These metrics give a comprehensive and quantitative measure of the ability of a marker to correctly classify germplasm as QTL[+]/[–], particularly against a background of high allelic diversity. Markers that score well on these metrics will have far higher reliability in breeding, and deficiencies in specific metrics give information on circumstances under which a marker may not be reliable. The metrics are applicable across different marker types and platforms, allowing an objective comparison of the performance of different markers irrespective of the platform. Evaluating markers using these metrics demonstrates that trait-specific markers consistently out-perform markers designed for other purposes. These metrics also provide a superb set of criteria for designing superior marker systems for a target QTL, enabling the selection of an optimal marker set before committing to design.

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<![CDATA[A cation diffusion facilitator, GmCDF1, negatively regulates salt tolerance in soybean]]> https://www.researchpad.co/article/5c3d00f4d5eed0c48403708b

Salt stress is one of the major abiotic factors that affect the metabolism, growth and development of plants, and soybean [Glycine max (L.) Merr.] germination is sensitive to salt stress. Thus, to ensure the successful establishment and productivity of soybeans in saline soil, the genetic mechanisms of salt tolerance at the soybean germination stage need to be explored. In this study, a population of 184 recombinant inbred lines (RILs) was utilized to map quantitative trait loci (QTLs) related to salt tolerance. A major QTL related to salt tolerance at the soybean germination stage named qST-8 was closely linked with the marker Sat_162 and detected on chromosome 8. Interestingly, a genome-wide association study (GWAS) identified several single nucleotide polymorphisms (SNPs) significantly associated with salt tolerance in the same genetic region on chromosome 8. Resequencing, bioinformatics and gene expression analyses were implemented to identify the candidate gene Glyma.08g102000, which belongs to the cation diffusion facilitator (CDF) family and was named GmCDF1. Overexpression and RNA interference of GmCDF1 in soybean hairy roots resulted in increased sensitivity and tolerance to salt stress, respectively. This report provides the first demonstration that GmCDF1 negatively regulates salt tolerance by maintaining K+-Na+ homeostasis in soybean. In addition, GmCDF1 affected the expression of two ion homeostasis-associated genes, salt overly sensitive 1 (GmSOS1) and Na+/H+ exchanger 1 (GmNHX1), in transgenic hairy roots. Moreover, a haplotype analysis detected ten haplotypes of GmCDF1 in 31 soybean genotypes. A candidate-gene association analysis showed that two SNPs in GmCDF1 were significantly associated with salt tolerance and that Hap1 was more sensitive to salt stress than Hap2. The results demonstrated that the expression level of GmCDF1 was negatively correlated with salt tolerance in the 31 soybean accessions (r = -0.56, P < 0.01). Taken together, these results not only indicate that GmCDF1 plays a negative role in soybean salt tolerance but also help elucidate the molecular mechanisms of salt tolerance and accelerate the breeding of salt-tolerant soybean.

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<![CDATA[Screening and verification of genes associated with leaf angle and leaf orientation value in inbred maize lines]]> https://www.researchpad.co/article/5c141eefd5eed0c484d28e63

Leaf angle and leaf orientation value are important traits affecting planting density and photosynthetic efficiency. To identify the genes involved in controlling leaf angle and leaf orientation value, we utilized 1.49×106 single nucleotide polymorphism (SNP) markers obtained after sequencing 80 backbone inbred maize lines in Jilin Province, based on phenotype data from two years, and analyzed these two traits in a genome-wide association study (GWAS). A total of 33 SNPs were significantly associated (P<0.000001) with the two target traits. Twenty-two SNPs were significantly associated with leaf angle and distributed on chromosomes 1, 3, 4, 5, 6, 7, 8, and 9, explaining 21.62% of the phenotypic variation. Eleven SNPs were significantly associated with leaf orientation value and distributed on chromosomes 1, 3, 4, 5, 6, 7, and 9, explaining 29.63% of the phenotypic variation. Within the mean linkage disequilibrium (LD) distance of 9.7 kb for the significant SNP locus, 22 leaf angle candidate genes were detected, and 3 of these candidate genes harbored significant SNPs, with phenotype contribution rates greater than 10%. Two candidate genes at distances less than 100 bp from significant SNPs showed phenotype contribution rates greater than 8%. Seven leaf orientation value candidate genes were detected: 3 of these candidate genes harbored significant SNPs, with phenotype contribution rates greater than 10%. Eight inbred maize lines with significant differences in leaf angle and leaf orientation value were selected to test candidate gene expression levels from 182 recombinant inbred lines (RILs). The 5 leaf angle candidate genes and 3 leaf orientation value candidate genes were verified using quantitative real-time PCR (qRT-PCR). The results showed significant differences in the expression levels of the above eight genes between inbred maize lines with significant differences in leaf angle and leaf orientation value.

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<![CDATA[β-composite Interval Mapping for robust QTL analysis]]> https://www.researchpad.co/article/5c0ed76ed5eed0c484f1411a

Interval mapping approaches have been playing significant role for quantitative trait locus (QTL) mapping to discover genetic architecture of diseases or traits with molecular markers. Composite interval mapping (CIM) is one of the superior approaches of the interval mapping for discovering both linked and unlinked putative QTL positions. However, estimators of this approach are not robust against phenotypic outliers. As a result, it fails to detect true QTL positions in presence of outliers. In this study, we investigated the performance of β-Composite Interval Mapping (BetaCIM) for detecting both linked and unlinked important QTLs positions from the robustness points of views. Performance of this approach depends on the value of tuning parameter β. It reduces to the classical CIM approach for β →0. We described and formulated the cross-validation procedure for selecting trait specific optimum value of β. It was observed that the optimum value of β depends on both amount of contaminated observations and their scatteredness. BetaCIM approach discover similar QTL positions as classical IM/CIM in absence of phenotypic outliers, but gives better results in presence of phenotypic outliers in terms of detecting true QTLs and effects estimation. We formulated the generalized forms of robust QTL analysis and developed an R-package named “BetaCIM” by implementing this robust approach. Left and right kidney weight data sets of mouse intercross population (129 S1/SvlmJ × A/J) were analyzed by using BetaCIM, CIM, and IM approaches. For right kidney weight (RKW) CIM and BetaCIM provided similar LOD score profile, and both approaches identified 3 QTL positions. IM approach also identified 3 QTL positions. For left kidney weight (LKW), there was evidence of one outlying observation; and in this case the BetaCIM approach identified 2 QTL positions. However, none of the QTLs were significant by CIM and IM approaches at 5% level of significance. Gene expression ontology (GEO) search showed that the candidate genes (Otof and A330033J07Rik) of the identified QTLs for LKW were expressed in kidney. Both simulation and real data analysis results showed that BetaCIM approach improves the performance over the existing methods in presence of phenotypic outliers. Otherwise, it keeps almost equal performance.

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<![CDATA[Genetic architecture and selective sweeps after polygenic adaptation to distant trait optima]]> https://www.researchpad.co/article/5bfc6225d5eed0c484ec6d60

Understanding the genetic basis of phenotypic adaptation to changing environments is an essential goal of population and quantitative genetics. While technological advances now allow interrogation of genome-wide genotyping data in large panels, our understanding of the process of polygenic adaptation is still limited. To address this limitation, we use extensive forward-time simulation to explore the impacts of variation in demography, trait genetics, and selection on the rate and mode of adaptation and the resulting genetic architecture. We simulate a population adapting to an optimum shift, modeling sequence variation for 20 QTL for each of 12 different demographies for 100 different traits varying in the effect size distribution of new mutations, the strength of stabilizing selection, and the contribution of the genomic background. We then use random forest regression approaches to learn the relative importance of input parameters in determining a number of aspects of the process of adaptation, including the speed of adaptation, the relative frequency of hard sweeps and sweeps from standing variation, or the final genetic architecture of the trait. We find that selective sweeps occur even for traits under relatively weak selection and where the genetic background explains most of the variation. Though most sweeps occur from variation segregating in the ancestral population, new mutations can be important for traits under strong stabilizing selection that undergo a large optimum shift. We also show that population bottlenecks and expansion impact overall genetic variation as well as the relative importance of sweeps from standing variation and the speed with which adaptation can occur. We then compare our results to two traits under selection during maize domestication, showing that our simulations qualitatively recapitulate differences between them. Overall, our results underscore the complex population genetics of individual loci in even relatively simple quantitative trait models, but provide a glimpse into the factors that drive this complexity and the potential of these approaches for understanding polygenic adaptation.

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<![CDATA[Linkage mapping of yeast cross protection connects gene expression variation to a higher-order organismal trait]]> https://www.researchpad.co/article/5c032de1d5eed0c4844f88ad

Gene expression variation is extensive in nature, and is hypothesized to play a major role in shaping phenotypic diversity. However, connecting differences in gene expression across individuals to higher-order organismal traits is not trivial. In many cases, gene expression variation may be evolutionarily neutral, and in other cases expression variation may only affect phenotype under specific conditions. To understand connections between gene expression variation and stress defense phenotypes, we have been leveraging extensive natural variation in the gene expression response to acute ethanol in laboratory and wild Saccharomyces cerevisiae strains. Previous work found that the genetic architecture underlying these expression differences included dozens of “hotspot” loci that affected many transcripts in trans. In the present study, we provide new evidence that one of these expression QTL hotspot loci affects natural variation in one particular stress defense phenotype—ethanol-induced cross protection against severe doses of H2O2. A major causative polymorphism is in the heme-activated transcription factor Hap1p, which we show directly impacts cross protection, but not the basal H2O2 resistance of unstressed cells. This provides further support that distinct cellular mechanisms underlie basal and acquired stress resistance. We also show that Hap1p-dependent cross protection relies on novel regulation of cytosolic catalase T (Ctt1p) during ethanol stress in a wild oak strain. Because ethanol accumulation precedes aerobic respiration and accompanying reactive oxygen species formation, wild strains with the ability to anticipate impending oxidative stress would likely be at an advantage. This study highlights how strategically chosen traits that better correlate with gene expression changes can improve our power to identify novel connections between gene expression variation and higher-order organismal phenotypes.

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<![CDATA[Construction of High-Density Linkage Maps of Populus deltoides × P. simonii Using Restriction-Site Associated DNA Sequencing]]> https://www.researchpad.co/article/5989db2cab0ee8fa60bd1673

Although numerous linkage maps have been constructed in the genus Populus, they are typically sparse and thus have limited applications due to low throughput of traditional molecular markers. Restriction-site associated DNA sequencing (RADSeq) technology allows us to identify a large number of single nucleotide polymorphisms (SNP) across genomes of many individuals in a fast and cost-effective way, and makes it possible to construct high-density genetic linkage maps. We performed RADSeq for 299 progeny and their two parents in an F1 hybrid population generated by crossing the female Populus deltoides ‘I-69’ and male Populus simonii ‘L3’. A total of 2,545 high quality SNP markers were obtained and two parent-specific linkage maps were constructed. The female genetic map contained 1601 SNPs and 20 linkage groups, spanning 4,249.12 cM of the genome with an average distance of 2.69 cM between adjacent markers, while the male map consisted of 940 SNPs and also 20 linkage groups with a total length of 3,816.24 cM and an average marker interval distance of 4.15 cM. Finally, our analysis revealed that synteny and collinearity are highly conserved between the parental linkage maps and the reference genome of P. trichocarpa. We demonstrated that RAD sequencing is a powerful technique capable of rapidly generating a large number of SNPs for constructing genetic maps in outbred forest trees. The high-quality linkage maps constructed here provided reliable genetic resources to facilitate locating quantitative trait loci (QTLs) that control growth and wood quality traits in the hybrid population.

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<![CDATA[HvDep1 Is a Positive Regulator of Culm Elongation and Grain Size in Barley and Impacts Yield in an Environment-Dependent Manner]]> https://www.researchpad.co/article/5989da5eab0ee8fa60b907c5

Heterotrimeric G proteins are intracellular membrane-attached signal transducers involved in various cellular processes in both plants and animals. They consist of three subunits denoted as α, β and γ. The γ-subunits of the so-called AGG3 type, which comprise a transmembrane domain, are exclusively found in plants. In model species, these proteins have been shown to participate in the control of plant height, branching and seed size and could therefore impact the harvestable yield of various crop plants. Whether AGG3-type γ-subunits influence yield in temperate cereals like barley and wheat remains unknown. Using a transgenic complementation approach, we show here that the Scottish malting barley cultivar (cv.) Golden Promise carries a loss-of-function mutation in HvDep1, an AGG3-type subunit encoding gene that positively regulates culm elongation and seed size in barley. Somewhat intriguingly, agronomic field data collected over a 12-year period reveals that the HvDep1 loss-of-function mutation in cv. Golden Promise has the potential to confer either a significant increase or decrease in harvestable yield depending on the environment. Our results confirm the role of AGG3-type subunit-encoding genes in shaping plant architecture, but interestingly also indicate that the impact HvDep1 has on yield in barley is both genotypically and environmentally sensitive. This may explain why widespread exploitation of variation in AGG3-type subunit-encoding genes has not occurred in temperate cereals while in rice the DEP1 locus is widely exploited to improve harvestable yield.

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