scholarly journals Regions of Chromosome 2A of Bread Wheat (Triticum aestivum L.) Associated with Variation in Physiological and Agronomical Traits under Contrasting Water Regimes

Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1023
Author(s):  
Tatyana A. Pshenichnikova ◽  
Svetlana V. Osipova ◽  
Olga G. Smirnova ◽  
Irina N. Leonova ◽  
Marina D. Permyakova ◽  
...  

Understanding the genetic architecture of drought tolerance is of great importance for overcoming the negative impact of drought on wheat yield. Earlier, we discovered the critical role of chromosome 2A for the drought-tolerant status of wheat spring cultivar Saratovskaya 29. A set of 92 single-chromosome recombinant double haploid (SCRDH) lines were obtained in the genetic background of Saratovskaya 29. The lines carry fragments of chromosome 2A from the drought-sensitive cultivar Yanetzkis Probat. The SCRDH lines were used to identify regions on chromosome 2A associated with the manifestation of physiological and agronomical traits under distinct water supply, and to identify candidate genes that may be associated with adaptive gene networks in wheat. Genotyping was done with Illumina Infinium 15k wheat array using 590 SNP markers with 146 markers being polymorphic. In four identified regions of chromosome 2A, 53 out of 58 QTLs associated with physiological and agronomic traits under contrasting water supply were mapped. Thirty-nine candidate genes were identified, of which 18 were transcription factors. The region 73.8–78.1 cM included the largest number of QTLs and candidate genes. The variation in SNPs associated with agronomical and physiological traits revealed among the SCRDH lines may provide useful information for drought related marker-assisted breeding.

2019 ◽  
Author(s):  
Waltram Ravelombola ◽  
Jun Qin ◽  
Ainong Shi ◽  
Fengmin Wang ◽  
Yan Feng ◽  
...  

Abstract Background Soybean [ Glycine max (L.) Merr.] is a legume of great interest worldwide. Enhancing genetic gain for agronomic traits via molecular approaches has been long considered as the main task for soybean breeders and geneticists. The objectives of this study were to evaluate maturity, plant height, seed weight, and yield in a diverse soybean accession panel, to conduct a genome-wide association study (GWAS) for these traits and identify SNP markers associated with the four traits, and to assess genomic selection (GS) accuracy. Results A total of 250 soybean accessions were evaluated for maturity, plant height, seed weight, and yield over three years. This panel was genotyped with a total of 10,259 high quality SNPs postulated from genotyping by sequencing (GBS). GWAS was performed using a Bayesian Information and Linkage Disequilibrium Iteratively Nested Keyway (BLINK) model, and GS was evaluated using a ridge regression best linear unbiased predictor (rrBLUP) model. The results revealed that a total of 20, 31, 37, 31, and 23 SNPs were significantly associated with the average 3-year data for maturity, plant height, seed weight, and yield, respectively; some significant SNPs were mapped into previously described loci ( E2 , E4 , and Dt1 ) affecting maturity and plant height in soybean and a new locus mapped on chromosome 20 was significantly associated with plant height; Glyma.10g228900 , Glyma.19g200800 , Glyma.09g196700 , and Glyma.09g038300 were candidate genes found in the vicinity of the top or the second best SNP for maturity, plant height, seed weight, and yield, respectively; a 11.5-Mb region of chromosome 10 was associated with both seed weight and yield; and GS accuracy was trait-, year-, and population structure-dependent. Conclusions The SNP markers identified from this study for plant height, maturity, seed weight and yield can be used to improve the four agronomic traits through marker-assisted selection (MAS) and GS in soybean breeding programs. After validation, the candidate genes can be transferred to new cultivars using SNP markers through MAS. The high GS accuracy has confirmed that the four agronomic traits can be selected in molecular breeding through GS.


2021 ◽  
Author(s):  
Fahad Alotaibi ◽  
Rahmah N. Al-Qthanin ◽  
Maha Aljabri ◽  
Mohammed Albaqami ◽  
Salah Abou-Elwafa

Abstract Soil salinity is a major environmental stress that adversely impacts the growth, development, productivity and quality of crop species, in particular, in arid and semi-arid regions. Identification of chromosomal regions associated with agronomic traits under salinity stress is crucial for improving salinity tolerance in wheat. GWAS and structure analyses were employed to evaluate 289 elite lines of the Wheat Association Mapping Initiative (WAMI) population under low (LS) and high (HS) salinity conditions using 15,737 SNP markers and seven agronomical traits. Evaluated genotypes responded differently to the different environments in all measured phenotypic traits, highlighting genetic diversity within the WAMI population in response to salt stress. Heritability degree ranged from moderate (37%) to high (88%). GWAS identified 118 and 120 significant associations between SNP markers and seven evaluated phenotypic traits under LS and HS conditions, respectively. Significant association of some markers with more than one phenotypic trait was observed, indicating possible pleiotropic or indirect effects. A high degree of significant linkage disequilibrium (> 52%) was observed among SNP markers on different chromosomes indicating epistatic interaction. The salt stress index (STI) exhibited a positive significant correlation to grain yield per plant (GYP) under both LS and HS conditions (R2 = 0.851–0.856). A linear regression between STI and GYP under HS conditions (GYPs) was identified, suggest that STI is the best tolerance index for predicting high yielding-genotypes. The results present the WAMI population as a valuable source for improving yield potential for salt tolerance in wheat. Furthermore, our findings emphasize that GWAS is a powerful tool in promoting wheat breeding through accurate identification of molecular markers significantly associated with agronomic traits, which is essential for marker-assisted breeding.


2021 ◽  
Vol 12 ◽  
Author(s):  
Lihua Wang ◽  
Hari D. Upadhyaya ◽  
Jian Zheng ◽  
Yanlong Liu ◽  
Shailesh Kumar Singh ◽  
...  

Panicle morphology is an important trait in racial classification and can determine grain yield and other agronomic traits in sorghum. In this study, we performed association mapping of panicle length, panicle width, panicle compactness, and peduncle recurving in the sorghum mini core panel measured in multiple environments with 6,094,317 single nucleotide polymorphism (SNP) markers. We mapped one locus each on chromosomes 7 and 9 to recurving peduncles and eight loci for panicle length, panicle width, and panicle compactness. Because panicle length was positively correlated with panicle width, all loci for panicle length and width were colocalized. Among the eight loci, two each were on chromosomes 1, 2, and 6, and one each on chromosomes 8 and 10. The two loci on chromosome 2, i.e., Pm 2-1 and Pm 2-2, were detected in 7 and 5 out of 11 testing environments, respectively. Pm 2-2 colocalized with panicle compactness. Candidate genes were identified from both loci. The rice Erect Panicle2 (EP2) ortholog was among the candidate genes in Pm 2-2. EP2 regulates panicle erectness and panicle length in rice and encodes a novel plant-specific protein with unknown functions. The results of this study may facilitate the molecular identification of panicle morphology-related genes and the enhancement of yield and adaptation in sorghum.


2021 ◽  
Vol 12 ◽  
Author(s):  
Hongchun Xiong ◽  
Yuting Li ◽  
Huijun Guo ◽  
Yongdun Xie ◽  
Linshu Zhao ◽  
...  

Agronomic traits such as heading date (HD), plant height (PH), thousand grain weight (TGW), and spike length (SL) are important factors affecting wheat yield. In this study, we constructed a high-density genetic linkage map using the Wheat55K SNP Array to map quantitative trait loci (QTLs) for these traits in 207 recombinant inbred lines (RILs). A total of 37 QTLs were identified, including 9 QTLs for HD, 7 QTLs for PH, 12 QTLs for TGW, and 9 QTLs for SL, which explained 3.0–48.8% of the phenotypic variation. Kompetitive Allele Specific PCR (KASP) markers were developed based on sequencing data and used for validation of the stably detected QTLs on chromosomes 3A, 4B and 6A using 400 RILs. A QTL cluster on chromosome 4B for PH and TGW was delimited to a 0.8 Mb physical interval explaining 12.2–22.8% of the phenotypic variation. Gene annotations and analyses of SNP effects suggested that a gene encoding protein Photosynthesis Affected Mutant 68, which is essential for photosystem II assembly, is a candidate gene affecting PH and TGW. In addition, the QTL for HD on chromosome 3A was narrowed down to a 2.5 Mb interval, and a gene encoding an R3H domain-containing protein was speculated to be the causal gene influencing HD. The linked KASP markers developed in this study will be useful for marker-assisted selection in wheat breeding, and the candidate genes provide new insight into genetic study for those traits in wheat.


2015 ◽  
Vol 5 (1) ◽  
pp. 578-590
Author(s):  
Charlotte TONESSIA ◽  
N'Dri KOUASSI ◽  
Ndiaga CISSE ◽  
Severin Aké

Single nucleotide polymorphism (SNP) markers were used to develop a genetic-linkage map and to identify QTLsinvolved in the genetic variation of agronomical traits in cowpeaunder two water regimes. A total of 1536 SNP GoldenGate assay were used to screen for polymorphism in a cowpea population of recombinant inbred lines. A total of 299 SNP markers amplified polymorphic products of which 228 mapped to the 11 cowpea linkage groups with an average distance of 6.5 cM between markers. The new SNP genetic map with a total length of 1281,8 cM were aligned with the consensus cowpea map allowing filling some gaps, which will increase QTLs analysis. A total of 31 QTLs affecting agronomic traits were identified and mapped to cowpea genomic regions. Among them 45% explaining from 3 to 35% of genetic variation were detected for both water conditions. Co-locations between QTLs were identified on several linkage groups among them QTLs affecting harvest index (HI) and grain yield suggesting their common genetic bases. Because, HI has been shown as the most stable and highly correlated parameter with cowpea yield under stress; our results will enable the efficiency of MAS and enhance genetic progress in cowpea.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Gehendra Bhattarai ◽  
Wei Yang ◽  
Ainong Shi ◽  
Chunda Feng ◽  
Braham Dhillon ◽  
...  

Abstract Background Downy mildew, the most devastating disease of spinach (Spinacia oleracea L.), is caused by the oomycete Peronospora effusa [=P. farinosa f. sp. spinaciae]. The P. effusa shows race specificities to the resistant host and comprises 19 reported races and many novel isolates. Sixteen new P. effusa races were identified during the past three decades, and the new pathogen races are continually overcoming the genetic resistances used in commercial cultivars. A spinach breeding population derived from the cross between cultivars Whale and Lazio was inoculated with P. effusa race 16 in an environment-controlled facility; disease response was recorded and genotyped using genotyping by sequencing (GBS). The main objective of this study was to identify resistance-associated single nucleotide polymorphism (SNP) markers from the cultivar Whale against the P. effusa race 16. Results Association analysis conducted using GBS markers identified six significant SNPs (S3_658,306, S3_692697, S3_1050601, S3_1227787, S3_1227802, S3_1231197). The downy mildew resistance locus from cultivar Whale was mapped to a 0.57 Mb region on chromosome 3, including four disease resistance candidate genes (Spo12736, Spo12784, Spo12908, and Spo12821) within 2.69–11.28 Kb of the peak SNP. Conclusions Genomewide association analysis approach was used to map the P. effusa race 16 resistance loci and identify associated SNP markers and the candidate genes. The results from this study could be valuable in understanding the genetic basis of downy mildew resistance, and the SNP marker will be useful in spinach breeding to select resistant lines.


Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1295
Author(s):  
Ahossi Patrice Koua ◽  
Mirza Majid Baig ◽  
Benedict Chijioke Oyiga ◽  
Jens Léon ◽  
Agim Ballvora

Nitrogen (N) is a vital component of crop production. Wheat yield varies significantly under different soil available N. Knowing how wheat responds to or interacts with N to produce grains is essential in the selection of N use efficient cultivars. We assessed in this study variations among wheat genotypes for productivity-related traits under three cropping systems (CS), high-nitrogen with fungicide (HN-WF), high-nitrogen without fungicide (HN-NF) and low-nitrogen without fungicide (LN-NF) in the 2015, 2016 and 2017 seasons. ANOVA results showed genotypes, CS, and their interactions significantly affected agronomic traits. Grain yield (GY) increased with higher leaf chlorophyll content, importantly under CS without N and fungicide supply. Yellow rust disease reduced the GY by 20% and 28% in 2015 and 2016, respectively. Moreover, averaged over growing seasons, GY was increased by 23.78% under CS with N supply, while it was greatly increased, by 52.84%, under CS with both N and fungicide application, indicating a synergistic effect of N and fungicide on GY. Fungicide supply greatly improved the crop ability to accumulate N during grain filling, and hence the grain protein content. Recently released cultivars outperformed the older ones in most agronomic traits including GY. Genotype performance and stability analysis for GY production showed differences in their stability levels under the three CS. The synergistic effect of nitrogen and fungicide on grain yield (GY) and the differences in yield stability levels of recently released wheat cultivars across three CS found in this study suggest that resource use efficiency can be improved via cultivar selection for targeted CS.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jose Miguel Soriano ◽  
Pasqualina Colasuonno ◽  
Ilaria Marcotuli ◽  
Agata Gadaleta

AbstractThe genetic improvement of durum wheat and enhancement of plant performance often depend on the identification of stable quantitative trait loci (QTL) and closely linked molecular markers. This is essential for better understanding the genetic basis of important agronomic traits and identifying an effective method for improving selection efficiency in breeding programmes. Meta-QTL analysis is a useful approach for dissecting the genetic basis of complex traits, providing broader allelic coverage and higher mapping resolution for the identification of putative molecular markers to be used in marker-assisted selection. In the present study, extensive QTL meta-analysis was conducted on 45 traits of durum wheat, including quality and biotic and abiotic stress-related traits. A total of 368 QTL distributed on all 14 chromosomes of genomes A and B were projected: 171 corresponded to quality-related traits, 127 to abiotic stress and 71 to biotic stress, of which 318 were grouped in 85 meta-QTL (MQTL), 24 remained as single QTL and 26 were not assigned to any MQTL. The number of MQTL per chromosome ranged from 4 in chromosomes 1A and 6A to 9 in chromosome 7B; chromosomes 3A and 7A showed the highest number of individual QTL (4), and chromosome 7B the highest number of undefined QTL (4). The recently published genome sequence of durum wheat was used to search for candidate genes within the MQTL peaks. This work will facilitate cloning and pyramiding of QTL to develop new cultivars with specific quantitative traits and speed up breeding programs.


2021 ◽  
Vol 22 (7) ◽  
pp. 3477
Author(s):  
Julia Zaborowska ◽  
Bartosz Łabiszak ◽  
Annika Perry ◽  
Stephen Cavers ◽  
Witold Wachowiak

Mountain plants, challenged by vegetation time contractions and dynamic changes in environmental conditions, developed adaptations that help them to balance their growth, reproduction, survival, and regeneration. However, knowledge regarding the genetic basis of species adaptation to higher altitudes remain scarce for most plant species. Here, we attempted to identify such corresponding genomic regions of high evolutionary importance in two closely related European pines, Pinus mugo and P. uncinata, contrasting them with a reference lowland relative—P. sylvestris. We genotyped 438 samples at thousands of single nucleotide polymorphism (SNP) markers, tested their genetic differentiation and population structure followed by outlier detection and gene ontology annotations. Markers clearly differentiated the species and uncovered patterns of population structure in two of them. In P. uncinata three Pyrenean sites were grouped together, while two outlying populations constituted a separate cluster. In P. sylvestris, Spanish population appeared distinct from the remaining four European sites. Between mountain pines and the reference species, 35 candidate genes for altitude-dependent selection were identified, including such encoding proteins responsible for photosynthesis, photorespiration and cell redox homeostasis, regulation of transcription, and mRNA processing. In comparison between two mountain pines, 75 outlier SNPs were found in proteins involved mainly in the gene expression and metabolism.


Pathogens ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 778
Author(s):  
Jana Bubenikova ◽  
Leona Vychodilova ◽  
Karla Stejskalova ◽  
Jan Futas ◽  
Jan Oppelt ◽  
...  

Feline coronavirus (FCoV) is a complex pathogen causing feline infectious peritonitis (FIP). Host genetics represents a factor contributing to the pathogenesis of the disease. Differential susceptibility of various breeds to FIP was reported with controversial results. The objective of this study was to compare the genetic diversity of different breeds on a panel of candidate genes potentially affecting FCoV infection. One hundred thirteen cats of six breeds were genotyped on a panel of sixteen candidate genes. SNP allelic/haplotype frequencies were calculated; pairwise FST and molecular variance analyses were performed. Principal coordinate (PCoA) and STRUCTURE analyses were used to infer population structure. Interbreed differences in allele frequencies were observed. PCoA analysis performed for all genes of the panel indicated no population substructure. In contrast to the full marker set, PCoA of SNP markers associated with FCoV shedding (NCR1 and SLX4IP) showed three clusters containing only alleles associated with susceptibility to FCoV shedding, homozygotes and heterozygotes for the susceptibility alleles, and all three genotypes, respectively. Each cluster contained cats of multiple breeds. Three clusters of haplotypes were identified by PCoA, two clusters by STRUCTURE. Haplotypes of a single gene (SNX5) differed significantly between the PCoA clusters.


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