Genome-wide analysis for root and leaf architecture traits associated with drought tolerance at the seedling stage in a highly ecologically diverse wheat population

Drought stress occurred at early growth stages in wheat affecting the following growth stages. Therefore, selecting promising drought-tolerant genotypes with highly adapted traits at the seedling stage is an important task for wheat breeders and geneticists. Few research efforts were conducted on the genetic control for drought-adaptive traits at the seedling stage in wheat. In this study, a set of 146 highly diverse spring wheat core collections representing 28 different countries was evaluated under drought stress at the seedling stage. All genotypes were exposed to drought stress for 13 days by water withholding. Leaf traits including seedling length, leaf wilting, days to wilting, leaf area, and leaf rolling were scored. Moreover, root traits such as root length, maximum width, emergence angle, tip angle, and number of roots were scored. Considerable significant genetic variation was found among all genotypes tested in these experiments. The heritability estimates ranged from 0.74 (leaf witling) to 0.99 (root tip angle). A set of nine genotypes were selected and considered drought-tolerant genotypes. Among all leaf traits, shoot length had significant correlations with all root traits under drought stress. The 146 genotypes were genotyped using the Infinium Wheat 15 K single nucleotide polymorphism (SNP) array and diversity arrays technology (DArT) marker platform. The result of genotyping revealed 12,999 SNPs and 2150 DArT markers which were used to run a genome-wide association study (GWAS). The results of GWAS revealed 169 markers associated with leaf and root traits under drought stress. Out of the 169 markers, 82 were considered major quantitative trait loci (QTL). The GWAS revealed 95 candidate genes were identified with 53 genes showing evidence for drought tolerance in wheat, while the remaining candidate genes were considered novel. No shared markers were found between leaf and root traits. The results of the study provided mapping novel markers associated with new root traits at the seedling stage. Also, the selected genotypes from different countries could be employed in future wheat breeding programs not only for improving adaptive drought-tolerant traits but also for expanding genetic diversity.

Development of miRNA-SSR and target-SSR markers from yield-associate genes and their applicability in the assessment of genetic diversity and association mapping in rice (Oryza sativa L.)

The gene-derived functional markers are considered effective to use in marker-assisted breeding and genetic diversity analysis. As of now, no functional markers have been identified from miRNAs regulating yield traits. The miRNAs play a key role as regulators in controlling the candidate genes involved in grain yield improvement in rice. In this study, 13 miRNA-SSR and their target gene SSR markers were mined from 29 yield-responsive miRNA along with their 29 target genes in rice. The validation of these markers showed that four miRNA-SSRs and one target gene SSR markers had shown polymorphism among 120 diverse rice genotypes. The PIC values ranged from 0.25 (OsARF18-SSR) to 0.72 (miR408-SSR, miR172b-SSR, and miR396f-SSR) with an average value of 0.57. These polymorphic markers grouped 120 rice genotypes into 3 main clusters based on the levels of high genetic diversity. These markers also showed significant association with key yield traits. Among all, miR172b-SSR showed a strong association with plant height in two seasons. This investigation suggests that this new class of molecular markers has great potential in the characterization of rice germplasm by genetic diversity and population structure and in marker-assisted breeding for the development of high-yielding varieties.

Supplementary information

The online version contains supplementary material available at 10.1007/s11032-024-01462-z.

Genome-wide identification of the key kinesin genes during fiber and boll development in upland cotton (Gossypium hirsutum L.)

Kinesin is a kind of motor protein, which interacts with microtubule filaments and regulates cellulose synthesis. Cotton fiber is a natural model for studying the cellular development and cellulose synthesis. Therefore, a systematic research of kinesin gene family in cotton (Gossypium spp.) will be beneficial for both understanding the function of kinesin protein and assisting the fiber improvement. Here, we aimed to identify the key kinesin genes present in cotton by combining genome-wide expression profile data, association mapping, and public quantitative trait loci (QTLs) in upland cotton (G. hirsutum L.). Results showed that 159 kinesin genes, including 15 genes of the kinesin-13 gene subfamily, were identified in upland cotton; of which 157 kinesin genes can be traced back to the diploid ancestors, G. raimondii and G. arboreum. Using a combined analysis of public QTLs and genome-wide expression profile information, there were 29 QTLs co-localized together with 28 kinesin genes in upland cotton, including 10 kinesin-13 subfamily genes. Genome-wide expression profile data indicated that, among the 28 co-localized genes, seven kinesin genes were predominantly expressed in fibers or ovules. By association mapping analysis, 30 kinesin genes were significantly associated with three fiber traits, among which a kinesin-13 gene, Ghir_A11G028430, was found to be associated with both cotton boll length and lint weight, and one kinesin-7 gene, Ghir_D04G017880 (Gh_Kinesin7), was significantly associated with fiber strength. In addition, two missense mutations were identified in the motor domain of the Gh_Kinesin7 protein. Overall, the kinesin gene family seemingly plays an important role in cotton fiber and boll development. The exploited kinesin genes will be beneficial for the genetic improvement of fiber quality and yield.

Genome-wide association study of drought tolerance in wheat (Triticum aestivum L.) identifies SNP markers and candidate genes

Drought stress poses a severe threat to global wheat production, necessitating an in-depth exploration of the genetic basis for drought tolerance associated traits. This study employed a 90 K SNP array to conduct a genome-wide association analysis, unravelling genetic determinants of key traits related to drought tolerance in wheat, namely plant height, root length, and root and shoot dry weight. Using the mixed linear model (MLM) method on 125 wheat accessions subjected to both well-watered and drought stress treatments, we identified 53 SNPs significantly associated with stress susceptibility (SSI) and tolerance indices (STI) for the targeted traits. Notably, chromosomes 2A and 3B stood out with ten and nine associated markers, respectively. Across 17 chromosomes, 44 unique candidate genes were pinpointed, predominantly located on the distal ends of 1A, 1B, 1D, 2A, 3A, 3B, 4A, 6A, 6B, 7A, 7B, and 7D chromosomes. These genes, implicated in diverse functions related to plant growth, development, and stress responses, offer a rich resource for future investigation. A clustering pattern emerged, notably with seven genes associated with SSI for plant height and four genes linked to both STI of plant height and shoot dry weight, converging on specific regions of chromosome arms of 2AS and 3BL. Additionally, shared genes encoding polygalacturonase, auxilin-related protein 1, peptide deformylase, and receptor-like kinase underscored the interconnectedness between plant height and shoot dry weight. In conclusion, our findings provide insights into the molecular mechanisms governing wheat drought tolerance, identifying promising genomic loci for further exploration and crop improvement strategies.

Dissection of figured wood trait in curly birch (Betula pendula Roth var. carelica (Mercklin) Hämet-Ahti) using high-throughput genotyping

Curly (Karelian) birch is a special variety of Betula pendula Roth distributed in the northwestern part of Europe. Karelian birch is well-known for its valuable figured curly wood also known as "wooden marble". The genetic basis underlying curly wood formation has been debated since last century, however, there was no data about loci responsible for the curly wood trait. In the present study, we analyzed two full-sibs populations derived from experimental crosses of curly birches and segregating for the trait. RADseq genotyping was applied to reveal how many loci are involved in 'curliness' formation and to search for genetic variants associated with this trait. One single interval on chromosome 10 was detected containing possible candidate genes. InDel marker BpCW1 was suggested for the first time for marker-assisted selection of trees with curly wood at their earliest stages of development.

Genotyping SNPs in lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2) exhibits association with wood density in teak (Tectona grandis L.f.)

BACKGROUND

Teak (Tectona grandis L.f.), an important source of tropical timber with immense economic value, is a highly outcrossing forest tree species. 150 unrelated accessions of teak (Tectona grandis L.f.) plus trees assembled as clones at National Teak Germplasm Bank, Chandrapur, Maharashtra, India was investigated for association mapping of candidate lignin biosynthesis gene (CAD1) and transcription factors (MYB1 and MYB2).

METHODS AND RESULTS

The CAD1, MYB1 and MYB2 were amplified using specifically designed primers. The amplified sequences were then sequenced and genotyped for 112 SNPs/11 indels. We evaluated the association between SNPs and wood density in teak accessions using GLM and MLM statistical models, with Bonferroni correction applied. The teak accessions recorded an average wood density of 416.69 kg.m-3 (CV 4.97%) and comprised of three loosely structured admixed sub-populations (K = 3), containing 72.05% genetic variation within sub-populations with low intragenic LD (0-21% SNP pairs) at P < 0.05 and high LD decay (33-934 bp) at R2 = 0.1. GLM and MLM models discounting systematic biases (Q and K matrices) to avoid false discovery revealed five loci at rare variants (MAF 0.003) and three loci at common variants (MAF 0.05) to be significantly (P < 0.05) associated with the wood density. However, the stringent Bonferroni correction (4.06-7.04 × 10-4) yielded only a single associated locus (B1485C/A) from exon of MYB1 transcription factor, contributing to about 10.35% phenotypic variation in wood density trait.

CONCLUSION

Scored SNP locus (B1485C/A) can be developed as a molecular probe for selection of improved planting stock with proven wood density trait for a large-scale teak plantation.

Genome-wide identification of the key Kinesin genes during fiber and boll development in upland cotton (Gossypium hirsutum L)

Kinesin is a kind of motor protein, which interacts with microtubule filaments and regulates cellulose synthesis. Cotton fiber is a natural model for studying the cellular development and cellulose synthesis. Therefore, a systematic research of Kinesin gene family in cotton (Gossypium spp.) will be beneficial for both understanding the function of Kinesin protein and assisting the fiber improvement. Here, we aimed to identify the key Kinesin genes present in cotton by combining genome-wide expression profile data, association mapping, and public quantitative trait loci (QTLs) in upland cotton (Gossypium hirsutum L.). Results showed that 159 Kinesin genes, including 15 genes of the Kinesin-13 gene subfamily, were identified in upland cotton; of which 157 Kinesin genes can be traced back to the diploid ancestors, G. raimondii and G. arboreum. Using a combined analysis of public QTLs and genome-wide expression profile information, there were 29 QTLs co-localized together with 28 Kinesin genes in upland cotton, including 10 Kinesin-13 subfamily genes. Genome-wide expression profile data indicated that, among the 28 co-localized genes, seven Kinesin genes were predominantly expressed in fibers or ovules. By association mapping analysis, 30 Kinesin genes were significantly associated with three fiber traits, among which a Kinesin-13 gene, Ghir_A11G028430, was found to be associated with both cotton boll length and lint weight, and one Kinesin-7 gene, Ghir_D04G017880 (Gh_Kinesin7), was significantly associated with fiber strength. In addition, two missense mutations were identified in the motor domain of the Gh_Kinesin7 protein. Overall, the Kinesin gene family seemingly plays an important role in cotton fiber and boll development. The exploited Kinesin genes will be beneficial for the genetic improvement of fiber quality and yield.

Identification of novel sources of partial and incomplete hypersensitive resistance to rust and associated genomic regions in common bean

Common bean (Phaseolus vulgaris) is one of the legume crops most consumed worldwide and bean rust is one of the most severe foliar biotrophic fungal diseases impacting its production. In this work, we searched for new sources of rust resistance (Uromyces appendiculatus) in a representative collection of the Portuguese germplasm, known to have accessions with an admixed genetic background between Mesoamerican and Andean gene pools. We identified six accessions with incomplete hypersensitive resistance and 20 partially resistant accessions of Andean, Mesoamerican, and admixed origin. We detected 11 disease severity-associated single-nucleotide polymorphisms (SNPs) using a genome-wide association approach. Six of the associations were related to partial (incomplete non-hypersensitive) resistance and five to incomplete hypersensitive resistance, and the proportion of variance explained by each association varied from 4.7 to 25.2%. Bean rust severity values ranged from 0.2 to 49.1% and all the infection types were identified, reflecting the diversity of resistance mechanisms deployed by the Portuguese germplasm.The associations with U. appendiculatus partial resistance were located in chromosome Pv08, and with incomplete hypersensitive resistance in chromosomes Pv06, Pv07, and Pv08, suggesting an oligogenic inheritance of both types of resistance. A resolution to the gene level was achieved for eight of the associations. The candidate genes proposed included several resistance-associated enzymes, namely β-amylase 7, acyl-CoA thioesterase, protein kinase, and aspartyl protease. Both SNPs and candidate genes here identified constitute promising genomics targets to develop functional molecular tools to support bean rust resistance precision breeding.

Genetic architecture of ear traits based on association mapping and co-expression networks in maize inbred lines and hybrids

Ear traits are key contributors to grain yield in maize; therefore, exploring their genetic basis facilitates the improvement of grain yield. However, the underlying molecular mechanisms of ear traits remain obscure in both inbred lines and hybrids. Here, two association panels, respectively, comprising 203 inbred lines (IP) and 246 F1 hybrids (HP) were employed to identify candidate genes for six ear traits. The IP showed higher phenotypic variation and lower phenotypic mean than the HP for all traits, except ear tip-barrenness length. By conducting a genome-wide association study (GWAS) across multiple environments, 101 and 228 significant single-nucleotide polymorphisms (SNPs) associated with six ear traits were identified in the IP and HP, respectively. Of these significant SNPs identified in the HP, most showed complete-incomplete dominance and over-dominance effects for each ear trait. Combining a gene co-expression network with GWAS results, 186 and 440 candidate genes were predicted in the IP and HP, respectively, including known ear development genes ids1 and sid1. Of these, nine candidate genes were detected in both populations and expressed in maize ear and spikelet tissues. Furthermore, two key shared genes (GRMZM2G143330 and GRMZM2G171139) in both populations were found to be significantly associated with ear traits in the maize Goodman diversity panel with high-density variations. These findings advance our knowledge of the genetic architecture of ear traits between inbred lines and hybrids and provide a valuable resource for the genetic improvement of ear traits in maize.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01426-9.

Exploring genetic diversity and ascertaining genetic loci associated with important fruit quality traits in apple (Malus × domestica Borkh.)

Genetic diversity is the primary source of variability in any crop improvement program, and the diverse germplasm of any crop species represents an important genetic resource for gene or allele mining to meet future needs. Huge genetic and phenotypic diversity is present in the apple gene pool, even though, breeding programs have been mainly focused on a few traits of interests, which have resulted in the reduction of the diversity in the cultivated lines of apple. Therefore, the present study was carried out on 70 diverse apple genotypes with the objective of analyzing the genetic diversity and to identify the genetic loci associated with important fruit quality traits. A total of 140 SSR primers were used to characterize the 70 genotypes of apples, out of which only 88 SSRs were found to be polymorphic. The PIC values varied from 0.03 to 0.75. The value of MI, EMR, and RP varied from 0.03 to 3.5, 0.5 to 5.0, and 1.89 to 6.74, respectively. The dendrogram and structure analysis divided all the genotypes into two main groups. In addition to this, large phenotypic variability was observed for the fruit quality traits under study indicated the suitability of the genotypes for association studies. Altogether 71 novel MTAs were identified for 10 fruit quality traits, of which 15 for fruit length, 15 for fruit diameter, 12 for fruit weight, 2 for total sugar, 2 for TSS, 4 for reducing sugar, 5 for non-reducing sugar, 5 for fruit firmness, 5 for fruit acidity and 6 for anthocyanin, respectively. Consistent with the physicochemical evaluation of traits, there was a significant correlation coefficient among different fruit quality characters, and many common markers were found to be associated with these traits (fruit diameter, length, TSS, total sugar, acidity and anthocyanin, respectively) by using the different modeling techniques (GLM, MLM). The inferred genetic structure, diversity pattern and the identified MTAs will be serving as resourceful grounds for better predictions and understanding of apple genome towards efficient conservation and utilization of apple germplasm for facilitating genetic improvement of fruit quality traits. Furthermore, these findings also suggested that association mapping could be a viable alternative to the conventional QTL mapping approach in apple.

Graphic abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-023-01382-w.

Identification of genetic loci for early maturity in spring bread wheat using the association analysis and gene dissection

Background

Early maturity in spring bread wheat is highly desirable in the regions where it enables the plants to evade high temperatures and plant pathogens at the end of the growing season.

Methods

To reveal the genetic loci responsible for the maturity time association analysis was carried out based on phenotyping for an 11-year period and high-throughput SNP genotyping of a panel of the varieties contrasting for this trait. The expression of candidate genes was verified using qPCR. The association between the SNP markers and the trait was validated using the biparental F2:3 population.

Results

Our data showed that under long-day conditions, the period from seedling to maturity is mostly influenced by the time from heading to maturity, rather than the heading time. The QTLs associated with the trait were located on 2A, 3B, 4A, 5B, 7A and 7B chromosomes with the 7BL locus being the most significant and promising for its SNPs accelerated the maturity time by about 9 days. Gene dissection in this locus detected a number of candidates, the best being TraesCS7B02G391800 (bZIP9) and TraesCS7B02G412200 (photosystem II reaction center). The two genes are predominantly expressed in the flag leaf while flowering. The effect of the SNPs was verified in F2:3 population and confirmed the association of the 4A, 5B and 7BL loci with the maturity time.

Delineation of novel genomic loci and putative candidate genes associated with seed iron and zinc content in lentil (Lens culinaris Medik.)

The use of molecular breeding approaches for development of lentil genotypes biofortified with essential micro-nutrients such as iron and zinc, could serve as a promising solution to address the problem of global malnutrition. Thus, genome-wide association study (GWAS) strategy was adopted in this study to identify the genomic regions associated with seed iron and zinc content in lentil. A panel of 95 diverse lentil genotypes, grown across three different geographical locations and evaluated for seed iron and zinc content, exhibited a wide range of variation. Genotyping-by-sequencing (GBS) analysis of the panel identified 33,745 significant single nucleotide polymorphisms (SNPs) that were distributed across all the 7 lentil chromosomes. Association mapping revealed 23 SNPs associated with seed iron content that were distributed across all the chromosomes except chromosome 3. Similarly, 14 SNPs associated with seed zinc content were also identified that were distributed across chromosomes 1, 2, 4, 5 and 6. Further, 80 genes were identified in the proximity of iron associated markers and 36 genes were identified in the proximity of zinc associated markers. Functional annotation of these genes revealed their putative involvement in iron and zinc metabolism. For seed iron content, two highly significant SNPs were found to be located within two putative candidate genes namely iron-sulfur cluster assembly (ISCA) and flavin binding monooxygenase (FMO) respectively. For zinc content, a highly significant SNP was detected in a gene encoding UPF0678 fatty acid-binding protein. Expression analysis of these genes and their putative interacting partners suggests their involvement in iron and zinc metabolism in lentil. Overall, in this study we have identified markers, putative candidate genes and predicted putative interacting protein partners significantly associated with iron and zinc metabolism that could be utilized in future breeding studies of lentil for nutrient biofortification.

Genetic analysis of the variation for mineral accumulation in the leaves and seeds of natural germplasm of Brassica rapa L. (AA) and the its derived forms extracted from an allotetraploid B.juncea L.(AABB)

Brassica rapa L. (2n = 20; AA) is a vegetable and oilseed crop that is grown all over the world. Its leaves, shoots, and seeds store significant amounts of minerals. We used inductively coupled plasma-optical emission spectroscopy (ICP-OES) to determine the concentrations of eleven minerals in the leaves and seeds of 195 advanced generation inbred lines, of which 92 represented natural (NR) B. rapa and the remaining 103 were derived (DR) from a set of mother genotypes originally extracted from an allotetraploid B. juncea (2n = 36; AABB). The inbred lines differed for the composition of leaf and seed minerals. Leaf concentrations of N, K, Zn, and Se were higher in the DR subpanel as compared to NR subpanel, along with high seed accumulations of K and Se. DArT genotyping and genome wide association mapping led to the identification of SNPs associated with leaf and seed mineral compositions. Chromosomes A03, A05, and A10 harboured the most associated loci. Annotations of the regions adjacent to respective GWAS peaks allowed prediction of genes known for acquisition, transport, and accumulation of minerals and heavy metal detoxification. Transcriptome analysis revealed differential expression patterns of the predicted candidates, with most genes either down-regulated in derived genotypes relative to natural forms or their expression being comparable between the two. General downregulation may be a consequence of extracting B. rapa from allotetraploid B. juncea through genome resection. Some of the identified SNPs may be used as DNA markers for breeding programmes designed to modify the leaf and seed mineral compositions.

Genome-wide association studies: an intuitive solution for SNP identification and gene mapping in trees

Analysis of natural diversity in wild/cultivated plants can be used to understand the genetic basis for plant breeding programs. Recent advancements in DNA sequencing have expanded the possibilities for genetically altering essential features. There have been several recently disclosed statistical genetic methods for discovering the genes impacting target qualities. One of these useful methods is the genome-wide association study (GWAS), which effectively identifies candidate genes for a variety of plant properties by examining the relationship between a molecular marker (such as SNP) and a target trait. Conventional QTL mapping with highly structured populations has major limitations. The limited number of recombination events results in poor resolution for quantitative traits. Only two alleles at any given locus can be studied simultaneously. Conventional mapping approach fails to work in perennial plants and vegetatively propagated crops. These limitations are sidestepped by association mapping or GWAS. The flexibility of GWAS comes from the fact that the individuals being examined need not be linked to one another, allowing for the use of all meiotic and recombination events to increase resolution. Phenotyping, genotyping, population structure analysis, kinship analysis, and marker-trait association analysis are the fundamental phases of GWAS. With the rapid development of sequencing technologies and computational methods, GWAS is becoming a potent tool for identifying the natural variations that underlie complex characteristics in crops. The use of high-throughput sequencing technologies along with genotyping approaches like genotyping-by-sequencing (GBS) and restriction site associated DNA (RAD) sequencing may be highly useful in fast-forward mapping approach like GWAS. Breeders may use GWAS to quickly unravel the genomes through QTL and association mapping by taking advantage of natural variances. The drawbacks of conventional linkage mapping can be successfully overcome with the use of high-resolution mapping and the inclusion of multiple alleles in GWAS.

Genome-wide association mapping of resistance to the foliar diseases septoria nodorum blotch and tan spot in a global winter wheat collection

Septoria nodorum blotch (SNB) and tan spot, caused by the necrotrophic fungal pathogens Parastagonospora nodorum and Pyrenophora tritici-repentis, respectively, often occur together as a leaf spotting disease complex on wheat (Triticum aestivum L.). Both pathogens produce necrotrophic effectors (NEs) that contribute to the development of disease. Here, genome-wide association analysis of a diverse panel of 264 winter wheat lines revealed novel loci on chromosomes 5A and 5B associated with sensitivity to the NEs SnTox3 and SnTox5 in addition to the known sensitivity genes for NEs Ptr/SnToxA, SnTox1, SnTox3, and SnTox5. Sensitivity loci for SnTox267 and Ptr ToxB were not detected. Evaluation of the panel with five P. nodorum isolates for SNB development indicated the Snn3-SnTox3 and Tsn1-SnToxA interactions played significant roles in disease development along with additional QTL on chromosomes 2A and 2D, which may correspond to the Snn7-SnTox267 interaction. For tan spot, the Tsc1-Ptr ToxC interaction was associated with disease caused by two isolates, and a novel QTL on chromosome 7D was associated with a third isolate. The Tsn1-ToxA interaction was associated with SNB but not tan spot. Therefore some, but not all, of the previously characterized host gene-NE interactions in these pathosystems play significant roles in disease development in winter wheat. Based on these results, breeders should prioritize the selection of resistance alleles at the Tsc1, Tsn1, Snn3, and Snn7 loci as well as the 2A and 7D QTL to obtain good levels of resistance to SNB and tan spot in winter wheat.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01400-5.

Genome-wide association studies and transcriptome sequencing analysis reveal novel genes associated with Al tolerance in wheat

Aluminum (Al) toxicity is a major threat to the productivity and quality of wheat on acid soil. Identifying novel Al tolerance genes is crucial for breeders to pyramid different tolerance mechanisms thus leading to greater Al tolerance. We aim to identify novel quantitative trait loci (QTL) and key candidate genes associated with Al tolerance in wheat. Herein, we investigated the genotypic variation in Al tolerance among 334 wheat varieties using an acid soil assay. Genome-wide association study (GWAS) and transcriptome were carried out to identify key genes for Al tolerance. GWAS identified several QTL associated with acid soil tolerance including one major QTL on chromosome 1A, in addition to the QTL on 4D where TaALMT1 is located. The four significant markers around the newly identified QTL explained 27.2% of the phenotypic variation. With the existence of reported markers for TaALMT1, more than 97% of the genotypes showed tolerance to Al. For those genotypes with the existence of the novel QTL on 1A but without TaALMT1, more than 90% of genotypes showed medium or high tolerance to Al, confirming the existence of the Al tolerance gene(s) on chromosome 1A. By combining GWAS and RNA-seq analysis, we identified 11 candidate genes associated with Al tolerance. The results provide new insights into the genetic basis of Al tolerance in wheat. The identified genes can be used for the breeding of Al tolerant accessions.

Exploring genomic regions involved in bread wheat resistance to leaf rust at seedling/adult stages by using GWAS analysis

BACKGROUND

Global wheat productivity is seriously challenged by a range of rust pathogens, especially leaf rust derived from Puccinia triticina. Since the most efficient approach to control leaf rust is genetic resistance, many efforts have been made to uncover resistance genes; however, it demands an ongoing exploration for effective resistance sources because of the advent of novel virulent races. Thus, the current study was focused on detecting leaf rust resistance-related genomic loci against the P. triticina prevalent races by GWAS in a set of Iranian cultivars and landraces.

RESULTS

Evaluation of 320 Iranian bread wheat cultivars and landraces against four prevalent rust pathotypes of P. triticina (LR-99-2, LR-98-12, LR-98-22, and LR-97-12) indicated the diversity in wheat accessions responses to P. triticina. From GWAS results, 80 leaf rust resistance QTLs were located in the surrounding known QTLs/genes on almost chromosomes, except for 1D, 3D, 4D, and 7D. Of these, six MTAs (rs20781/rs20782 associated with resistance to LR-97-12; rs49543/rs52026 for LR-98-22; rs44885/rs44886 for LR-98-22/LR-98-1/LR-99-2) were found on genomic regions where no resistance genes previously reported, suggesting new loci conferring resistance to leaf rust. The GBLUP genomic prediction model appeared better than RR-BLUP and BRR, reflecting that GBLUP is a potent model for genomic selection in wheat accessions.

CONCLUSIONS

Overall, the newly identified MTAs as well as the highly resistant accessions in the recent work provide an opportunity towards improving leaf rust resistance.

Screening germplasm and detecting QTLs for mesocotyl elongation trait in rice (Oryza sativa L.) by association mapping

BACKGROUND

Rice is one of the most important food crops in the world and mainly cultivated in paddy field by transplanting seedlings. However, increasing water scarcity due to climate change, labor cost for transplanting, and competition from urbanization is making this traditional method of rice production unsustainable in the long term. In the present study, we mined favorable alleles for mesocotyl elongation length (MEL) by combining the phenotypic data of 543 rice accessions with genotypic data of 262 SSR markers through association mapping method.

RESULTS

Among the 543 rice accessions studied, we found 130 accessions could elongate mesocotyl length under dark germination condition. A marker-trait association analysis based on a mixed linear model revealed eleven SSR markers were associated with MEL trait with p-value less than 0.01. Among the 11 association loci, seven were novel. In total, 30 favorable marker alleles for MEL were mined, and RM265-140 bp showed the highest phenotypic effect value of 1.8 cm with Yuedao46 as the carrier accession. The long MEL group of rice accessions had higher seedling emergence rate than the short MEL group in the field. The correlation coefficient (r ^GCC-FSC = 0.485**) between growth chamber condition (GCC) and field soil condition (FSC) showed positive relationship and highly significant (P < 0.01) indicating that the result obtained in GCC could basically represent that obtained under FSC.

CONCLUSION

Not every genotype of the rice possesses the ability to elongate its mesocotyl length under dark or deep sowing condition. Mesocotyl elongation length is a quantitative trait controlled by many gene loci, and can be improved by pyramiding favorable alleles dispersed at different loci in different germplasm into a single genotype.

Application of SolCAP Genotyping in Potato (Solanum tuberosum L.) Association Mapping

Potato variety development entails a number of breeding steps, as well as testing and, finally, commercialization. Historically, phenotypic assesment were carried out to select and germplasm development. The US Department of Agriculture (USDA) funded the Solanaceae Coordinated Agricultural Project (SolCAP) to decode genomic resources into tools that breeders and geneticists can use. This project resulted in the creation of a genome-wide single-nucleotide polymorphism (SNP) array that can be used to evaluate elite potato-breeding germplasm. This array was used to genotype a diverse panel of Solanum species, as well as numerous biparental, diploid, and tetraploid populations. It has high marker density to generate genetic maps that can be used to identify numerous quantitative trait loci (QTLs) for agronomic, quality, biotic, and abiotic resistance traits. Up to now, numerous QTLs for important traits have been identified using new diploid and tetraploid genetic maps. SNP markers were used to assess germplasm relationships and fingerprint varieties and identify candidate genes. The Infinium 8303 SolCAP Potato array offers a common set of SNP markers that can be used for mapping, germplasm assessment, and fingerprinting with confidence. This array has also been helpful in furthering our understanding of the potato genome. Furthermore, some other Infinium potato arrays (i.e., 12 K, 20 K, and 25 K) have been genotyped, and breeders can map quantitative trait loci (QTLs) across multiple populations to improve our understanding of economically important traits and lead to marker-assisted selection (MAS) and breeding and, ultimately, improved varieties.

Integrated genomic approaches delineate a novel role of ROP1 ENHANCER1 in controlling seed protein content of chickpea

Utilizing a combinatorial approach of quantitative trait locus (QTL)-Seq and candidate gene-based association mapping, the QTLs and genes responsible for seed protein content (SPC), a major quality trait in chickpea, were identified. Whole genome re-sequencing based QTL-Seq analysis of bulked recombinant inbred lines from a mapping population contrasting for SPC led to the identification of two QTLs [0.94 Mb on Linkage Group (LG)5 and 1.16 Mb on LG6] encompassing three SNPs, displaying the highest ΔSNP index. These highly significant SNPs and their associated genes were validated in 211 chickpea mini-core accessions varying in SPC, revealing a tightly associated marker affecting CaREN1 (ROP1 ENHANCER1) and explaining a phenotypic variation of 23%. This SNP was subsequently converted into a cost effective allele-specific PCR-based marker that could be utilized for rapid screening of SPC during marker assisted breeding. Furthermore, in planta functional validation via knockdown of CaREN1 transcripts led to significant reduction in SPC of chickpea. This decrease in seed protein is likely due to disruption in the formation of CaREN1 protein complexes comprising chaperones, phosphopeptide-binding proteins, and GTPases that mediate folding, transport and accumulation of seed storage proteins, as indicated through affinity purification-mass spectrometry. Taken together, our data will expedite tailoring of chickpea cultivars with augmented SPC.

Identification of genomic regions governing moisture and heat stress tolerance employing association mapping in rice (Oryza sativa L.)

BACKGROUND

Rice crop is damaged extremely by abiotic stress world-wide. The best approach to enhance drought tolerance in rice varieties is to identify and introgress yield QTLs with major effects. The Association mapping approach helps in the identification of genomic regions governing physiological, yield and yield attributes under moisture and heat stress conditions in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome.

METHODS AND RESULTS

The association mapping panel of 110 rice germplasm lines exhibited significant variation for all the traits in both irrigated and moisture stress conditions. The extent of yield reduction ranged to 83% during rabi, 2018-19, 53% in rabi, 2019-20 and 68% in pooled analysis. The genotypes Badami, Badshabhog, Pankaj, Varalu, Vasundhara, Vivekdhan, Krishna and Minghui63 exhibited drought tolerance with least yield penalty under moisture stress conditions. The genotypes Konark, MTU3626, NLR33671, PR118 and Triguna exhibited minimal reduction in heat stress tolerance traits. Association mapping of germplasm using 37808 SNP markers detected a total of 10 major MTA (Marker-trait association) clusters distributed on chromosomes 1, 3, 4 and 11 through mixed linear model (MLM) governing multiple traits from individual data analysis which are consistent across the years and situations. The pooled data generated a total of five MTA clusters located on chromosome 6. In addition, several novel unique MTAs were also identified. Heat stress analysis generated a total of 23 MTAs distributed on chromosomes 1, 5, 6 and 11. Candidate gene analysis detected a total of 53 and 38 genes under individual and pooled data analysis for various yield and yield attributes under control and moisture stress conditions, respectively and a total of 11 candidate genes in heat stress Conditions.

CONCLUSION

The major and novel MTAs identified in the present investigation for various drought and heat tolerant traits can be utilized for breeding climate-resilient rice varieties. The candidate genes predicted for key MTAs are of great value to deploy into the rice breeding after functional characterization.

Association mapping for protein, total soluble sugars, starch, amylose and chlorophyll content in rice

BACKGROUND

Protein, starch, amylose and total soluble sugars are basic metabolites of seed that influence the eating, cooking and nutritional qualities of rice. Chlorophyll is responsible for the absorption and utilization of the light energy influencing photosynthetic efficiency in rice plant. Mapping of these traits are very important for detection of more number of robust markers for improvement of these traits through molecular breeding approaches.

RESULTS

A representative panel population was developed by including 120 germplasm lines from the initial shortlisted 274 lines for mapping of the six biochemical traits using 136 microsatellite markers through association mapping. A wide genetic variation was detected for the traits, total protein, starch, amylose, total soluble sugars, chlorophyll a, and chlorophyll b content in the population. Specific allele frequency, gene diversity, informative markers and other diversity parameters obtained from the population indicated the effectiveness of utilization of the population and markers for mapping of these traits. The fixation indices values estimated from the population indicated the existence of linkage disequilibrium for the six traits. The population genetic structure at K = 3 showed correspondence with majority of the members in each group for the six traits. The reported QTL, qProt1, qPC6.2, and qPC8.2 for protein content; qTSS8.1 for total soluble sugar; qAC1.2 for amylose content; qCH2 and qSLCHH for chlorophyll a (Chl. a) while qChl5D for chlorophyll b (Chl. b) were validated in this population. The QTL controlling total protein content qPC1.2; qTSS7.1, qTSS8.2 and qTSS12.1 for total soluble sugars; qSC2.1, qSC2.2, qSC6.1 and qSC11.1 for starch content; qAC11.1, qAC11.2 and qAC11.3 for amylose content; qChla8.1 for Chl. a content and qChlb7.1 and qChlb8.1 for Chl. b identified by both Generalized Linear Model and Mixed Linear Model were detected as novel QTL. The chromosomal regions on chromosome 8 at 234 cM for grain protein content and total soluble sugars and at 363 cM for Chl. a and Chl. b along with the position at 48 cM on chromosome 11 for starch and amylose content are genetic hot spots for these traits.

CONCLUSION

The validated, co-localized and the novel QTL detected in this study will be useful for improvement of protein, starch, amylose, total soluble sugars and chlorophyll content in rice.

Genome-Wide Association Study (GWAS) and genome prediction of seedling salt tolerance in bread wheat (Triticum aestivum L.)

BACKGROUND

Salinity tolerance in wheat is imperative for improving crop genetic capacity in response to the expanding phenomenon of soil salinization. However, little is known about the genetic foundation underlying salinity tolerance at the seedling growth stage of wheat. Herein, a GWAS analysis was carried out by the random-SNP-effect mixed linear model (mrMLM) multi-locus model to uncover candidate genes responsible for salt tolerance at the seedling stage in 298 Iranian bread wheat accessions, including 208 landraces and 90 cultivars.

RESULTS

A total of 29 functional marker-trait associations (MTAs) were detected under salinity, 100 mM NaCl (sodium chloride). Of these, seven single nucleotide polymorphisms (SNPs) including rs54146, rs257, rs37983, rs18682, rs55629, rs15183, and rs63185 with R² ≥ 10% were found to be linked with relative water content, root fresh weight, root dry weight, root volume, shoot high, proline, and shoot potassium (K⁺), respectively. Further, a total of 27 candidate genes were functionally annotated to be involved in response to the saline environment. Most of these genes have key roles in photosynthesis, response to abscisic acid, cell redox homeostasis, sucrose and carbohydrate metabolism, ubiquitination, transmembrane transport, chromatin silencing, and some genes harbored unknown functions that all together may respond to salinity as a complex network. For genomic prediction (GP), the genomic best linear unbiased prediction (GBLUP) model reflected genetic effects better than both bayesian ridge regression (BRR) and ridge regression-best linear unbiased prediction (RRBLUP), suggesting GBLUP as a favorable tool for wheat genomic selection.

CONCLUSION

The SNPs and candidate genes identified in the current work can be used potentially for developing salt-tolerant varieties at the seedling growth stage by marker-assisted selection.

A Poisson reduced-rank regression model for association mapping in sequencing data

BACKGROUND

Single-cell RNA-sequencing (scRNA-seq) technologies allow for the study of gene expression in individual cells. Often, it is of interest to understand how transcriptional activity is associated with cell-specific covariates, such as cell type, genotype, or measures of cell health. Traditional approaches for this type of association mapping assume independence between the outcome variables (or genes), and perform a separate regression for each. However, these methods are computationally costly and ignore the substantial correlation structure of gene expression. Furthermore, count-based scRNA-seq data pose challenges for traditional models based on Gaussian assumptions.

RESULTS

We aim to resolve these issues by developing a reduced-rank regression model that identifies low-dimensional linear associations between a large number of cell-specific covariates and high-dimensional gene expression readouts. Our probabilistic model uses a Poisson likelihood in order to account for the unique structure of scRNA-seq counts. We demonstrate the performance of our model using simulations, and we apply our model to a scRNA-seq dataset, a spatial gene expression dataset, and a bulk RNA-seq dataset to show its behavior in three distinct analyses.

CONCLUSION

We show that our statistical modeling approach, which is based on reduced-rank regression, captures associations between gene expression and cell- and sample-specific covariates by leveraging low-dimensional representations of transcriptional states.

Combining datasets for maize root seedling traits increases the power of GWAS and genomic prediction accuracies

The identification of genomic regions associated with root traits and the genomic prediction of untested genotypes can increase the rate of genetic gain in maize breeding programs targeting roots traits. Here, we combined two maize association panels with different genetic backgrounds to identify single nucleotide polymorphisms (SNPs) associated with root traits, and used a genome-wide association study (GWAS) and to assess the potential of genomic prediction for these traits in maize. For this, we evaluated 377 lines from the Ames panel and 302 from the Backcrossed Germplasm Enhancement of Maize (BGEM) panel in a combined panel of 679 lines. The lines were genotyped with 232 460 SNPs, and four root traits were collected from 14-day-old seedlings. We identified 30 SNPs significantly associated with root traits in the combined panel, whereas only two and six SNPs were detected in the Ames and BGEM panels, respectively. Those 38 SNPs were in linkage disequilibrium with 35 candidate genes. In addition, we found higher prediction accuracy in the combined panel than in the Ames or BGEM panel. We conclude that combining association panels appears to be a useful strategy to identify candidate genes associated with root traits in maize and improve the efficiency of genomic prediction.

Genetic architecture of end-use quality traits in soft white winter wheat

Background

Genetic improvement of end-use quality is an important objective in wheat breeding programs to meet the requirements of grain markets, millers, and bakers. However, end-use quality phenotyping is expensive and laborious thus, testing is often delayed until advanced generations. To better understand the underlying genetic architecture of end-use quality traits, we investigated the phenotypic and genotypic structure of 14 end-use quality traits in 672 advanced soft white winter wheat breeding lines and cultivars adapted to the Pacific Northwest region of the United States.

Results

This collection of germplasm had continuous distributions for the 14 end-use quality traits with industrially significant differences for all traits. The breeding lines and cultivars were genotyped using genotyping-by-sequencing and 40,518 SNP markers were used for association mapping (GWAS). The GWAS identified 178 marker-trait associations (MTAs) distributed across all wheat chromosomes. A total of 40 MTAs were positioned within genomic regions of previously discovered end-use quality genes/QTL. Among the identified MTAs, 12 markers had large effects and thus could be considered in the larger scheme of selecting and fixing favorable alleles in breeding for end-use quality in soft white wheat germplasm. We also identified 15 loci (two of them with large effects) that can be used for simultaneous breeding of more than a single end-use quality trait. The results highlight the complex nature of the genetic architecture of end-use quality, and the challenges of simultaneously selecting favorable genotypes for a large number of traits. This study also illustrates that some end-use quality traits were mainly controlled by a larger number of small-effect loci and may be more amenable to alternate selection strategies such as genomic selection.

Conclusions

In conclusion, a breeder may be faced with the dilemma of balancing genotypic selection in early generation(s) versus costly phenotyping later on.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08676-5.

Genome-wide association mapping identifies an SNF4 ortholog that impacts biomass and sugar yield in sorghum and sugarcane

Sorghum is a feed/industrial crop in developed countries and a staple food elsewhere in the world. This study evaluated the sorghum mini core collection for days to 50% flowering (DF), biomass, plant height (PH), soluble solid content (SSC), and juice weight (JW), and the sorghum reference set for DF and PH, in 7-12 testing environments. We also performed genome-wide association mapping with 6 094 317 and 265 500 single nucleotide polymorphism markers in the mini core collection and the reference set, respectively. In the mini core panel we identified three quantitative trait loci for DF, two for JW, one for PH, and one for biomass. In the reference set panel we identified another quantitative trait locus for PH on chromosome 6 that was also associated with biomass, DF, JW, and SSC in the mini core panel. Transgenic studies of three genes selected from the locus revealed that Sobic.006G061100 (SbSNF4-2) increased biomass, SSC, JW, and PH when overexpressed in both sorghum and sugarcane, and delayed flowering in transgenic sorghum. SbSNF4-2 encodes a γ subunit of the evolutionarily conserved AMPK/SNF1/SnRK1 heterotrimeric complexes. SbSNF4-2 and its orthologs will be valuable in genetic enhancement of biomass and sugar yield in plants.

Recent status of Genotyping by Sequencing (GBS) Technology in cucumber (Cucumis sativus L.): a review

Current and advanced breeding tools are being used to improve economically important horticultural crops to meet the consumers' needs and preferences. Genotyping-by-sequencing (GBS) is an extremely useful tool in the investigation and analysis of the genetic diversity of different cultivars. Based on a broad range of genetic backgrounds like single nucleotide polymorphism (SNPs), GBS is known as a novel technique to facilitate the detection of quantitative trait loci (QTL) regions robustly linked with interested traits compared to genome-wide association study (GWAS) and QTL. GBS has gained popularity among breeders in recent years and it is also employed in cucumber breeding programs. Cucumbers (C. sativus L.) are monoecious, gynoecious and some of them are parthenocarpic species. Cucumber is one of the most economical and essential crops in the Cucurbitaceae family. For time immemorial, cucumber has been produced and consumed all over the world like other cucurbits. To a large extent, cultivated cucurbits are beneficial to human health for providing necessary minerals and fibers.Therefore, this review portrays the current status of advances made by using GBS and its combination with other tools in various studies of cucumber such as the use of GBS and single nucleotide polymorphism (SNP) markers, GBS and GWAS, also with QTL and marker-assisted selection (MAS) are applied to display and detect explicit genetic architecture complex traits in crops and chromosome rearrangements.Cucumber breeding programs have undoubtedly benefited from genotyping-by-sequencing. Using the GBS method, research discovered lots of new candidate genes that control various traits including spine color, fruit stalk-end color, and disease resistance in cucumber lines.

Association analysis of germination level cold stress tolerance and candidate gene identification in Upland cotton (Gossypium hirsutum L.)

Cotton originated from ancestors in the Gossypium genus that grew in semi-desert habitats. As a result, it is adversely affected by low temperatures especially during germination and the first weeks of growth. Despite this, there are relatively few molecular studies on cold stress in cotton. This limitation may present a future breeding handicap, as recent years have witnessed increased low temperature damage to cotton production. Cold tolerance is a sustainable approach to obtain good production in case of extreme cold. In the present study, 110 Upland cotton (Gossypium hirsutum) genotypes were evaluated for cold tolerance at the germination stage. We identified vigorous genotypes with cold-related parameters that outperformed the panel's average performance ( x ¯  = 76.9% CG, 83.9% CSI, 167.5 CWVI). Molecular genetic diversity analysis with 101 simple sequence repeat (SSR) markers yielding 416 loci was used to select tolerant genotypes that could be important materials for breeding this trait. A total of 16 marker-cold tolerance trait associations (p < 0.005) were identified with 10 of them having major effects (PVE > 10%). Based on the positions of these markers, candidate genes for cold tolerance in the G. hirsutum genome were identified. Three of these markers (BNL0569, CIR081 and CIR202) are important candidates for use in marker-assisted breeding for cold tolerance because they mapped to genes previously associated with cold tolerance in other plant species such as Arabidopsis thaliana, rice and tomato.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-022-01184-6.

Identification of potential MTAs and candidate genes for juice quality- and yield-related traits in Saccharum clones: a genome-wide association and comparative genomic study

Sugarcane is an economically important commercial crop which provides raw material for the production of sugar, jaggery, bioethanol, biomass and other by-products. Sugarcane breeding till today heavily relies on conventional breeding approaches which is time consuming, laborious and costly. Integration of marker-assisted selection (MAS) in sugarcane genetic improvement programs for difficult to select traits like sucrose content, resistance to pests and diseases and tolerance to abiotic stresses will accelerate varietal development. In the present study, association mapping approach was used to identify QTLs and genes associated with sucrose and other important yield-contributing traits. A mapping panel of 110 diverse sugarcane genotypes and 148 microsatellite primers were used for structured association mapping study. An optimal subpopulation number (ΔK) of 5 was identified by structure analysis. GWAS analysis using TASSEL identified a total of 110 MTAs which were localized into 27 QTLs by GLM and MLM (Q + K, PC + K) approaches. Among the 24 QTLs sequenced, 12 were able to identify potential candidate genes, viz., starch branching enzyme, starch synthase 4, sugar transporters and G3P-DH related to carbohydrate metabolism and hormone pathway-related genes ethylene insensitive 3-like 1, reversion to ethylene sensitive1-like, and auxin response factor associated to juice quality- and yield-related traits. Six markers, NKS 5_185, SCB 270_144, SCB 370_256, NKS 46_176 and UGSM 648_245, associated with juice quality traits and marker SMC31CUQ_304 associated with NMC were validated and identified as significantly associated to the traits by one-way ANOVA analysis. In conclusion, 24 potential QTLs identified in the present study could be used in sugarcane breeding programs after further validation in larger population. The candidate genes from carbohydrate and hormone response pathway presented in this study could be manipulated with genome editing approaches to further improve sugarcane crop.

Mapping Major Disease Resistance Genes in Soybean by Genome-Wide Association Studies

Soybean is one of the most valuable agricultural crops in the world. Besides, this legume is constantly attacked by a wide range of pathogens (fungi, bacteria, viruses, and nematodes) compromising yield and increasing production costs. One of the major disease management strategies is the genetic resistance provided by single genes and quantitative trait loci (QTL). Identifying the genomic regions underlying the resistance against these pathogens on soybean is one of the first steps performed by molecular breeders. In the past, genetic mapping studies have been widely used to discover these genomic regions. However, over the last decade, advances in next-generation sequencing technologies and their subsequent cost decreasing led to the development of cost-effective approaches to high-throughput genotyping. Thus, genome-wide association studies applying thousands of SNPs in large sets composed of diverse soybean accessions have been successfully done. In this chapter, a comprehensive review of the majority of GWAS for soybean diseases published since this approach was developed is provided. Important diseases caused by Heterodera glycines, Phytophthora sojae, and Sclerotinia sclerotiorum have been the focus of the several GWAS. However, other bacterial and fungi diseases also have been targets of GWAS. As such, this GWAS summary can serve as a guide for future studies of these diseases. The protocol begins by describing several considerations about the pathogens and bringing different procedures of molecular characterization of them. Advice to choose the best isolate/race to maximize the discovery of multiple R genes or to directly map an effective R gene is provided. A summary of protocols, methods, and tools to phenotyping the soybean panel is given to several diseases. We also give details of options of DNA extraction protocols and genotyping methods, and we describe parameters of SNP quality to soybean data. Websites and their online tools to obtain genotypic and phenotypic data for thousands of soybean accessions are highlighted. Finally, we report several tricks and tips in Subheading 4, especially related to composing the soybean panel as well as generating and analyzing the phenotype data. We hope this protocol will be helpful to achieve GWAS success in identifying resistance genes on soybean.

Biparental Crossing and QTL Mapping for Validation of Genome-Wide Association Studies

Association mapping (AM), also known as genome-wide association studies (GWAS), is increasingly being employed in crop plants for the identification of QTL/genes and marker-trait associations (MTAs) in natural populations. Large numbers of such associations have been identified for variety of traits in different crop plants. However, not many of these associations have been used practically in the crop improvement program due to lack of validation. Although there are different ways through which the results of AM/GWAS could be validated, the best approach is to develop a biparental population for the trait of interest. An overview of the steps involved in the validation of results of AM using biparental mapping population in plants is provided in this chapter.

Genome-wide association links candidate genes to fruit firmness, fruit flesh color, flowering time, and soluble solid content in apricot (Prunus armeniaca L.)

BACKGROUND

Apricots originated from China, Central Asia and the Near East and arrived in Anatolia, and particularly in their second homeland of Malatya province in Turkey. Apricots are outstanding summer fruits, with their beautiful attractive color, delicious sweet taste, aroma and high vitamin and mineral content.

METHODS AND RESULTS

In the current study, a total of 259 apricots genotypes from different geographical origins in Turkey were used. Significant variations were detected in fruit firmness (FF), fruit flesh color (FFC), flowering time (FT), and soluble solid content (SSC). A total of 11,532 SNPs based on DArT were developed and used in the analyses of population structure and association mapping (AM). According to the STRUCTURE (v.2.2) analysis, the apricot genotypes were divided into three groups. The mixed linear model with Q and K matrixes were used to detect the associations between the SNPs and four traits. A total of 131 SNPs were associated with FF, FFC and SSC. No SNP marker was detected associated with FT.

CONCLUSION

The results demonstrated that AM had high potential of revealing the markers associated with economically important traits in apricot. The SNPs identified in the study can be used in future breeding programs for marker-assisted selection in apricot.

Genome-wide association mapping uncovers sex-associated copy number variation markers and female hemizygous regions on the W chromosome in Salix viminalis

Background

Sex chromosomes are in some species largely undifferentiated (homomorphic) with restricted sex determination regions. Homomorphic but different sex chromosomes are found in the closely related genera Populus and Salix indicating flexible sex determination systems, ideal for studies of processes involved in sex chromosome evolution. We have performed genome-wide association studies of sex and analysed sex chromosomes in a population of 265 wild collected Salix viminalis accessions and studied the sex determining locus.

Results

A total of 19,592 markers were used in association analyses using both Fisher’s exact tests and a single-marker mixed linear model, which resulted in 48 and 41 sex-associated (SA) markers respectively. Across all 48 SA markers, females were much more often heterozygous than males, which is expected if females were the heterogametic sex. The majority of the SA markers were, based on positions in the S. purpurea genome, located on chromosome 15, previously demonstrated to be the sex chromosome. Interestingly, when mapping the genotyping-by-sequencing sequence tag harbouring the two SA markers with the highest significance to the S. viminalis genomic scaffolds, five regions of very high similarity were found: three on a scaffold that represents a part of chromosome 15, one on a scaffold that represents a part of chromosome 9 and one on a scaffold not anchored to the genome. Based on segregation differences of the alleles at the two marker positions and on differences in PCR amplification between females and males we conclude that females had multiple copies of this DNA fragment (chromosome 9 and 15), whereas males only had one (chromosome 9). We therefore postulate that the female specific sequences have been copied from chromosome 9 and inserted on chromosome 15, subsequently developing into a hemizygous W chromosome linked region.

Conclusions

Our results support that sex determination in S. viminalis is controlled by one locus on chromosome 15. The segregation patterns observed at the SA markers furthermore confirm that S. viminalis females are the heterogametic sex. We also identified a translocation from chromosome 9 to the W chromosome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08021-2.

Genome-wide association mapping reveals key genomic regions for physiological and yield-related traits under salinity stress in wheat (Triticum aestivum L.)

A genome-wide association study (GWAS) was conducted using six different multi-locus GWAS models and 35K SNP array to demarcate genomic regions underlying reproductive stage salinity tolerance. Marker-trait association analysis was performed for salt tolerance indices (STI) of 11 morpho-physiological traits, and the actual concentrations of Na⁺ and K⁺, and the Na⁺/K⁺ ratio in flag leaf. A total of 293 significantly associated quantitative trait nucleotides (QTNs) for 14 morpho-physiological traits were identified. Of these 293 QTNs, 12 major QTNs with R² ≥ 10.0% were detected in three or more GWAS models. Novel major QTNs were identified for plant height, number of effective tillers, biomass, grain yield, thousand grain weight, Na⁺ and K⁺ content, and the Na⁺/K⁺ ratio in flag leaf. Moreover, 48 candidate genes were identified from the associated genomic regions. The QTNs identified in this study could potentially be targeted for improving salinity tolerance in wheat.

Genetic basis of some physiological traits and yield in early and late sowing conditions in bread wheat (Triticum aestivum L.)

The rise in human population necessitates the use of all available tools to enhance wheat productivity. In this regard, pre-breeding has mobilized novel underutilized genetic variation into breeding programs. However, this germplasm needs to be characterized for its efficient utilization. This investigation was initiated to evaluate the early and late sown wheat pre-breeding germplasm for physiology- and yield-related traits and to associate the mapped SNPs using association mapping approach. Our results indicate that the germplasm performed better in early sowing in comparison to late planting where grain yield (Yd) was found positively correlated with water use efficiency (WUE), heading time, and chlorophyll contents (Chl). We discovered a total of 210 associations involving 155 SNPs. Taking into consideration either early or late sowing and the mean values, only 12 marker traits were associated with trait germination, plant height, stomatal conductance, transpiration rate, Chl, carotenoids, and Yd. Our correlations and mapping results indicate that higher WUE along with Chl can be targeted as indirect physiological markers to enhance wheat yield.

Transcriptome analysis and association mapping reveal the genetic regulatory network response to cadmium stress in Populus tomentosa

Long non-coding RNAs (lncRNAs) play essential roles in plant abiotic stress responses, but the response of lncRNA-mediated genetic networks to cadmium (Cd) treatment remain elusive in trees, the promising candidates for phytoremediation of Cd contamination. We identified 172 Cd-responsive lncRNAs and 295 differentially expressed target genes in the leaves of Cd-treated Populus tomentosa. Functional annotation revealed that these lncRNAs were involved in various processes, including photosynthesis, hormone regulation, and phenylalanine metabolism. Association studies identified 78 significant associations, representing 14 Cd-responsive lncRNAs and 28 target genes for photosynthetic and leaf physiological traits. Epistasis uncovered 83 pairwise interactions among these traits, revealing Cd-responsive lncRNA-mediated genetic networks for photosynthesis and leaf physiology in P. tomentosa. We focused on the roles of two Cd-responsive lncRNA-gene pairs, MSTRG.22608.1-PtoMYB73 and MSTRG.5634.1-PtoMYB27, in Cd tolerance of Populus, and detected insertions/deletions within lncRNAs as polymorphisms driving target gene expression. Genotype analysis of lncRNAs and heterologous overexpression of PtoMYB73 and PtoMYB27 in Arabidopsis indicated their effects on enhancing Cd tolerance, photosynthetic rate, and leaf growth, and the potential interaction mechanisms of PtoMYB73 with abiotic stresses. Our study identifies the genetic basis for the response of Populus to Cd treatment, facilitating genetic improvement of Cd tolerance in trees.

Different loci control resistance to different isolates of the same race of Colletotrichum lindemuthianum in common bean

Linkage and genome-wide association analyses using high-throughput SNP genotyping revealed different loci controlling resistance to different isolates of race 65 of Colletotrichum lindemuthianum in common bean. Development of varieties with durable resistance to anthracnose is a major challenge in common bean breeding programs because of the extensive virulence diversity of Colletotrichum lindemuthianum fungus. We used linkage and genome-wide association analyses to tap the genomic regions associated with resistance to different isolates of race 65. Linkage mapping was done using an F₂ population derived from the cross between the Mesoamerican common beans BRS Estilo x Ouro Vermelho, inoculated with two different isolates of race 65. Association genetics relied on a diversity common bean panel containing 189 common bean accessions inoculated with five different isolates of race 65 as an attempt to validate the linkage analysis findings and, eventually, identify other genomic regions associated with resistance to race 65. The F₂ population and diversity panel were genotyped with the BARCBean6K_3 Illumina BeadChip containing 5398 SNP markers. Both linkage and genome-wide association analyses identified different loci controlling resistance to different isolates of race 65 on linkage group Pv04. Genome-wide association analysis also detected loci on Pv05, Pv10 and Pv11 associated with resistance to race 65. These findings indicate that resistance to race 65 can be overcome by the virulence diversity among different isolates of the same race and could lead to the loss of resistance after cultivar release. We identified 25 resistant common bean cultivars to all five isolates of race 65 in the diversity panel. The accessions should be useful to develop cultivars combining different resistance genes that favor durable resistance to anthracnose in common bean.

GWAS revealed effect of genotype × environment interactions for grain yield of Nebraska winter wheat

Background

Improving grain yield in cereals especially in wheat is a main objective for plant breeders. One of the main constrains for improving this trait is the G × E interaction (GEI) which affects the performance of wheat genotypes in different environments. Selecting high yielding genotypes that can be used for a target set of environments is needed. Phenotypic selection can be misleading due to the environmental conditions. Incorporating information from phenotypic and genomic analyses can be useful in selecting the higher yielding genotypes for a group of environments.

Results

A set of 270 F_3:6 wheat genotypes in the Nebraska winter wheat breeding program was tested for grain yield in nine environments. High genetic variation for grain yield was found among the genotypes. G × E interaction was also highly significant. The highest yielding genotype differed in each environment. The correlation for grain yield among the nine environments was low (0 to 0.43). Genome-wide association study revealed 70 marker traits association (MTAs) associated with increased grain yield. The analysis of linkage disequilibrium revealed 16 genomic regions with a highly significant linkage disequilibrium (LD). The candidate parents’ genotypes for improving grain yield in a group of environments were selected based on three criteria; number of alleles associated with increased grain yield in each selected genotype, genetic distance among the selected genotypes, and number of different alleles between each two selected parents.

Conclusion

Although G × E interaction was present, the advances in DNA technology provided very useful tools and analyzes. Such features helped to genetically select the highest yielding genotypes that can be used to cross grain production in a group of environments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07308-0.

Assessing Rice Salinity Tolerance: From Phenomics to Association Mapping

Rice is the most salt-sensitive cereal, suffering yield losses above 50% with soil salinity of 6 dS/m. Thus, understanding the mechanisms of rice salinity tolerance is key to address food security. In this chapter, we provide guidelines to assess rice salinity tolerance using a high-throughput phenotyping platform (HTP) with digital imaging at seedling/early tillering stage and suggest improved analysis methods using stress indices. The protocols described here also include computer scripts for users to improve their experimental design, run genome-wide association studies (GWAS), perform multi-testing corrections, and obtain the Manhattan plots, enabling the identification of loci associated with salinity tolerance. Notably, the computer scripts provided here can be used for any stress or GWAS experiment and independently of HTP.

Association Mapping in Plants

Quantitative trait loci mapping has become a common practice in crop plants and can be accomplished using either biparental populations following interval mapping or natural populations following the approach of association mapping. Because of its ability to use the natural diversity and to search for functional variants in a broader germplasm, association mapping is becoming popular among researchers. An overview of the different steps involved in association mapping in plants is provided in this chapter.

Haplotype-based genome-wide association increases the predictability of leaf rust (Puccinia triticina) resistance in wheat

Resistance breeding is crucial for sustainable control of wheat leaf rust and single nucleotide polymorphism (SNP)-based genome-wide association studies (GWAS) are widely used to dissect leaf rust resistance. Unfortunately, GWAS based on SNPs often explained only a small proportion of the genetic variation. We compared SNP-based GWAS with a method based on functional haplotypes (FH) considering epistasis in a comprehensive hybrid wheat mapping population composed of 133 parents plus their 1574 hybrids and characterized with 626 245 high-quality SNPs. In total, 2408 and 1 139 828 significant associations were detected in the mapping population by using SNP-based and FH-based GWAS, respectively. These associations mapped to 25 and 69 candidate regions, correspondingly. SNP-based GWAS highlighted two already-known resistance genes, Lr22a and Lr34-B, while FH-based GWAS detected associations not only on these genes but also on two additional genes, Lr10 and Lr1. As revealed by a second hybrid wheat population for independent validation, the use of detected associations from SNP-based and FH-based GWAS reached predictabilities of 11.72% and 22.86%, respectively. Therefore, FH-based GWAS is not only more powerful for detecting associations, but also improves the accuracy of marker-assisted selection compared with the SNP-based approach.

Candidate gene association of gene expression data in sugarcane contrasting for sucrose content

Association mapping of gene expression data, generated from transcriptome and proteome studies, provides a means of understanding the functional significance and trait association potential of candidate genes. In this study, we applied candidate gene association mapping to validate sugarcane genes, using data from the starch and sucrose metabolism pathway, transcriptome, and proteome. We performed multiplex PCR targeted amplicon sequencing of 109 candidate genes, using NGS technology. A range of statistical models, both single-locus and multi-locus, were compared for minimization of false positives in association mapping of four sugar-related traits with different heritability. The Fixed and random model Circulating Probability Unification model effectively suppressed false positives for both low- and high-heritability traits. We identified favorable alleles of the candidate genes involved in signalling and transcriptional regulation. The results will support genetic improvement of sugarcane and may help clarify the genetic architecture of sugar-related traits.

Reference-free Association Mapping from Sequencing Reads Using k-mers

Association mapping is the process of linking phenotypes with genotypes. In genome wide association studies (GWAS), individuals are first genotyped using microarrays or by aligning sequenced reads to reference genomes. However, both these approaches rely on reference genomes which limits their application to organisms with no or incomplete reference genomes. To address this, reference free association mapping methods have been developed. Here we present the protocol of an alignment free method for association studies which is based on counting k-mers in sequenced reads, testing for associations between k-mers and the phenotype of interest, and local assembly of the k-mers of statistical significance. The method can map associations of categorical phenotypes to sequence and structural variations without requiring prior sequencing of reference genomes.

Genome-wide association mapping revealed numerous novel genomic loci for grain nutritional and yield-related traits in rice (Oryza sativa L.) landraces

A core set of 190 rice landraces were used to decipher the genetic structure and to discover the chromosomal regions containing QTLs, affecting the grain micro-nutrients, fatty acids, and yield-related traits by using 148 molecular markers in this study. Landraces were categorized into three sub-groups based on population stratification study and followed by neighbor-joining tree and principal component analysis. Analysis of variance revealed abundant variations among the landraces for studied traits with less influence of environmental factors. Genome Wide Association Studies (GWAS) revealed 22 significant and consistent QTLs through marker trait association (MTAs) for 12 traits based on 2 years and pooled analysis. Out of 22 QTLs, three have been reported earlier while 19 QTLs are novel. Interestingly, 13 QTLs out of 22 were explained more than 10% phenotypic variance. Association of RM1148 and RM205 with Days to 50% flowering was comparable with flowering control genes Ghd8/qDTH8 and qDTH9, respectively. Similarly, Zn content was associated with RM44, which is situated within the QTL qZn8-1. Moreover, significant association of RM25 with oleic acid content was closely positioned with QTL qOle8. Association of RM7434 with grain yield/plant; RM184 with spikelet fertility %; R3M10, R9M42 with hundred seed weight; RM536, RM17467, RM484, RM26063 with Fe content; RM44, RM6839 with Zn content are the major outcomes of this study. In addition, association of R11M23 with days to 50% flowering, panicle length and total spikelets per panicle are explained the possible occurrence of pleiotropism among these traits. Prominent rice landraces viz., Anjani (early maturity); Sihar (extra dwarf); Gangabaru (highest grain yield/plant); Karhani (highest iron content); Byalo-2 (highest zinc content) and Kadamphool (highest oleic acid) were identified through this study. The present study will open many avenues towards utilization of these QTLs and superior landraces in rice breeding for developing nutrition-rich high yielding varieties.

A GBS-based GWAS analysis of adaptability and yield traits in bread wheat (Triticum aestivum L.)

Wheat is a foremost food grain of Pakistan and occupies a vital position in agricultural policies of the country. Wheat demand will be increased by 60% by 2050 which is a serious concern to meet this demand. Conventional breeding approaches are not enough to meet the demand of growing human population. It is paramount to integrate underutilized genetic diversity into wheat gene pool through efficient and accurate breeding tools and technology. In this study, we present the genetic analysis of a 312 diverse pre-breeding lines using DArT-seq SNPs seeking to elucidate the genetic components of emergence percentage, heading time, plant height, lodging, thousand kernel weight, and yield (Yd) which resulted in detection of 201 significant (p value < 10^-3) and 61 highly significant associations (p value < 1.45 × 10^-4). More importantly, chromosomes 1B and 2A carried loci linked to Yd in two different seasons, and an increase of up to 8.20% is possible in Yd by positive allele mining. We identified seven lines with > 4 positive alleles for Yd whose pedigree carried Aegilops squarrosa as one of the parents providing evidence that Aegilops species, apart from imparting resistance against biotic stresses, may also provide alleles for yield enhancement.

Genetic dissection of eating and cooking qualities in different subpopulations of cultivated rice (Oryza sativa L.) through association mapping

Background

Eating and cooking qualities (ECQs) of rice (Oryza sativa L.) determine consumer acceptance and the economic value of rice varieties. The starch physicochemical properties, i.e. amylose content, gel consistency, gelatinization temperature and pasting viscosity are important indices for evaluating rice ECQs. Genetic factors are required for development of rice varieties with excellent ECQs and association mapping is one of the promising approaches for discovering such associated genetic factors.

Results

A genome-wide association mapping was performed on a set of 253 non-glutinous rice accessions consisting of 83 indica and 170 japonica cultivated rice varieties through phenotyping for 11 ECQ traits in two consecutive years and genotyping with 210 polymorphic SSR and candidate-gene markers. These markers amplified 747 alleles with an average of 3.57 alleles per locus. The structure, phylogenetic relationship, and principal component analysis indicated a strong population differentiation between indica and japonica accessions and association mapping was thus undertaken within indica and japonica subpopulations. All traits showed a large phenotypic variation and highly significant phenotypic correlations were present between most of traits. A total of 33 and 30 loci were located for 11 ECQs in indica and japonica subpopulations respectively. Most of associated loci were overlapped with starch synthesis-related genes (SSRGs), and the Wx locus gathered 14 associated loci with the largest effects on amylose content, gel consistency and pasting viscosities. Eight subpopulation specific markers, RM588, Wx-(CT)_n, SSI and SBE1 for indica subpopulation and RM550, Wx^mp, SSIIa and SBE4 for japonica subpopulation, were identified, suggesting alleles of SSRGs showed the subspecific tendency. Nevertheless, allelic variation in SSIIa showed no tendency towards subspecies. One associated maker RM550 detected in japonica subpopulation for amylose content and pasting viscosity was verified a potential novel and stably expressed locus and could be selected for further fine mapping.

Conclusion

This study illustrated the potential for dissecting genetic factors of complex traits in domesticated rice subspecies and provided highly associated markers to facilitate marker-assisted selection for breeding high-quality indica or japonica rice varieties.

Development of EST-SSR markers and association mapping with floral traits in Syringa oblata

BACKGROUND

Lilac (Syringa oblata) is an important woody plant with high ornamental value. However, very limited genetic marker resources are currently available, and little is known about the genetic architecture of important ornamental traits for S. oblata, which is hindering its genetic studies. Therefore, it is of great significance to develop effective molecular markers and understand the genetic architecture of complex floral traits for the genetic research of S. oblata.

RESULTS

In this study, a total of 10,988 SSRs were obtained from 9864 unigene sequences with an average of one SSR per 8.13 kb, of which di-nucleotide repeats were the dominant type (32.86%, 3611). A set of 2042 primer pairs were validated, out of which 932 (45.7%) exhibited successful amplifications, and 248 (12.1%) were polymorphic in eight S. oblata individuals. In addition, 30 polymorphic EST-SSR markers were further used to assess the genetic diversity and the population structure of 192 cultivated S. oblata individuals. Two hundred thirty-four alleles were detected, and the PIC values ranged from 0.23 to 0.88 with an average of 0.51, indicating a high level of genetic diversity within this cultivated population. The analysis of population structure showed two major subgroups in the association population. Finally, 20 significant associations were identified involving 17 markers with nine floral traits using the mixed linear model. Moreover, marker SO104, SO695 and SO790 had significant relationship with more than one trait.

CONCLUSION

The results showed newly developed markers were valuable resource and provided powerful tools for genetic breeding of lilac. Beyond that, our study could serve an efficient foundation for further facilitate genetic improvement of floral traits for lilac.

Identification of quantitative trait nucleotides and candidate genes for soybean seed weight by multiple models of genome-wide association study

BACKGROUND

Seed weight is a complex yield-related trait with a lot of quantitative trait loci (QTL) reported through linkage mapping studies. Integration of QTL from linkage mapping into breeding program is challenging due to numerous limitations, therefore, Genome-wide association study (GWAS) provides more precise location of QTL due to higher resolution and diverse genetic diversity in un-related individuals.

RESULTS

The present study utilized 573 breeding lines population with 61,166 single nucleotide polymorphisms (SNPs) to identify quantitative trait nucleotides (QTNs) and candidate genes for seed weight in Chinese summer-sowing soybean. GWAS was conducted with two single-locus models (SLMs) and six multi-locus models (MLMs). Thirty-nine SNPs were detected by the two SLMs while 209 SNPs were detected by the six MLMs. In all, two hundred and thirty-one QTNs were found to be associated with seed weight in YHSBLP with various effects. Out of these, seventy SNPs were concurrently detected by both SLMs and MLMs on 8 chromosomes. Ninety-four QTNs co-localized with previously reported QTL/QTN by linkage/association mapping studies. A total of 36 candidate genes were predicted. Out of these candidate genes, four hub genes (Glyma06g44510, Glyma08g06420, Glyma12g33280 and Glyma19g28070) were identified by the integration of co-expression network. Among them, three were relatively expressed higher in the high HSW genotypes at R5 stage compared with low HSW genotypes except Glyma12g33280. Our results show that using more models especially MLMs are effective to find important QTNs, and the identified HSW QTNs/genes could be utilized in molecular breeding work for soybean seed weight and yield.

CONCLUSION

Application of two single-locus plus six multi-locus models of GWAS identified 231 QTNs. Four hub genes (Glyma06g44510, Glyma08g06420, Glyma12g33280 & Glyma19g28070) detected via integration of co-expression network among the predicted candidate genes.

Genome-wide association mapping for resistance to leaf, stem, and yellow rusts of common wheat under field conditions of South Kazakhstan

Common or bread wheat (Triticum aestivum L.) is the most important cereal crop in the world, including Kazakhstan, where it is a major agricultural commodity. Fungal pathogens producing leaf, stem, and yellow (stripe) rusts of wheat may cause yield losses of up to 50-60%. One of the most effective methods for preventing these losses is to develop resistant cultivars with high yield potential. This goal can be achieved using complex breeding studies, including the identification of key genetic factors controlling rust disease resistance. In this study, a panel consisting of 215 common wheat cultivars and breeding lines from Kazakhstan, Russia, Europe, USA, Canada, Mexico, and Australia, with a wide range of resistance to leaf rust (LR), stem rust (SR), and yellow rust (YR) diseases, was analyzed under field conditions in Southern Kazakhstan. The collection was genotyped using the 20K Illumina iSelect DNA array, where 11,510 informative single-nucleotide polymorphism markers were selected for further genome-wide association study (GWAS). Evaluation of the phenotypic diversity over 2 years showed a mostly mixed reaction to LR, mixed reaction/moderate susceptibility to SR, and moderate resistance to YR among wheat accessions from Kazakhstan. GWAS revealed 45 marker-trait associations (MTAs), including 23 for LR, 14 for SR, and eight for YR resistances. Three MTAs for LR resistance and one for SR resistance appeared to be novel. The MTAs identified in this work can be used for marker-assisted selection of common wheat in Kazakhstan in breeding new cultivars resistant to LR, SR, and YR diseases. These findings can be helpful for pyramiding genes with favorable alleles in promising cultivars and lines.