Genome-wide association mapping identifies markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection

Fickett, Nathanael D.; Gutierrez, Andres; Verma, Mohit; Pontif, M. J.; Hale, Anna L.; Kimbeng, C. A.; Baisakh, Niranjan

doi:10.1016/j.ygeno.2018.12.002

Cited by 42 publications

(38 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The resulting regions were posteriorly adopted in other studies [101][102][103][104] due to the large quantity of markers with sufficient sequencing depth located in genic regions. Another approach is GBS 5,23,28,[105][106][107] , which is the preferred genotyping method for plants with some degree of genomic complexity 23,108 mainly due to its simplicity, reproducibility and considerable genome coverage 109 . In addition, regulatory regions controlling different phenotypes are often located in noncoding DNA, and GBS allows the amplification of such regions 50 .…”

Section: Discussionmentioning

confidence: 99%

“…Sequencing reads are generally organized by using the S. bicolor genome for comparative alignments and the subsequent identification of putative variants with bioinformatic methods. This reference choice is due to sorghum's phylogenetic proximity to sugarcane 5,28,[105][106][107] and, in some cases, probe experimental design [100][101][102][103][104] . Despite sorghum's genome usage, the availability of sugarcane pseudoreferences has provided new genomic tools for scientific research as initially explored by Balsalobre et al 23 , who used the sorghum genome, a sugarcane MF genome 65 , a sugarcane leaf transcriptome 51 and SUCEST tags 68 .…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance

Aono

Costa

Rody

et al. 2020

Sci Rep

View full text Add to dashboard Cite

Sugarcane is an economically important crop, but its genomic complexity has hindered advances in molecular approaches for genetic breeding. New cultivars are released based on the identification of interesting traits, and for sugarcane, brown rust resistance is a desirable characteristic due to the large economic impact of the disease. Although marker-assisted selection for rust resistance has been successful, the genes involved are still unknown, and the associated regions vary among cultivars, thus restricting methodological generalization. We used genotyping by sequencing of full-sib progeny to relate genomic regions with brown rust phenotypes. We established a pipeline to identify reliable SNPs in complex polyploid data, which were used for phenotypic prediction via machine learning. We identified 14,540 SNPs, which led to a mean prediction accuracy of 50% when using different models. We also tested feature selection algorithms to increase predictive accuracy, resulting in a reduced dataset with more explanatory power for rust phenotypes. As a result of this approach, we achieved an accuracy of up to 95% with a dataset of 131 SNPs related to brown rust QTL regions and auxiliary genes. Therefore, our novel strategy has the potential to assist studies of the genomic organization of brown rust resistance in sugarcane.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance

Aono

Costa

Rody

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…In addition, the SSR fragments are treated as dominant in polyploid species, such as sugarcane, and thus do not capture the allelic dosage information of homologous chromosomes [101]. Despite that Fickett et al [42] obtained 6299 SNPs and 235 InDels through a high-throughput genotyping system, only 27 markers were significantly associated with six traits (stalk number, stalk height, stalk diameter, °Brix, pol and fiber) and explained no more than 14.3% of the phenotypic variation. Therefore, genetic studies on polyploidy species, like sugarcane, are obviously delayed when compared to those on crops with minor genetic complexity.…”

Section: Discussionmentioning

confidence: 99%

“…In this context, single-dose markers, such as simple sequence repeats (SSRs) and target region amplification polymorphisms (TRAPs) could be used to characterize genome variation, investigate population structure and genetic diversity and thus enable GWAS [37,39–41]. In addition, despite the potential for using LD-based association studies to identify MTAs, a few studies on yield-related traits in sugarcane have been published [18,35–42].…”

Section: Introductionmentioning

confidence: 99%

A genome-wide association study identified loci for yield component traits in sugarcane (Saccharum spp.)

et al. 2019

View full text Add to dashboard Cite

Sugarcane ( Saccharum spp.) has a complex genome with variable ploidy and frequent aneuploidy, which hampers the understanding of phenotype and genotype relations. Despite this complexity, genome-wide association studies (GWAS) may be used to identify favorable alleles for target traits in core collections and then assist breeders in better managing crosses and selecting superior genotypes in breeding populations. Therefore, in the present study, we used a diversity panel of sugarcane, called the Brazilian Panel of Sugarcane Genotypes (BPSG), with the following objectives: (i) estimate, through a mixed model, the adjusted means and genetic parameters of the five yield traits evaluated over two harvest years; (ii) detect population structure, linkage disequilibrium (LD) and genetic diversity using simple sequence repeat (SSR) markers; (iii) perform GWAS analysis to identify marker-trait associations (MTAs); and iv) annotate the sequences giving rise to SSR markers that had fragments associated with target traits to search for putative candidate genes. The phenotypic data analysis showed that the broad-sense heritability values were above 0.48 and 0.49 for the first and second harvests, respectively. The set of 100 SSR markers produced 1,483 fragments, of which 99.5% were polymorphic. These SSR fragments were useful to estimate the most likely number of subpopulations, found to be four, and the LD in BPSG, which was stronger in the first 15 cM and present to a large extension (65 cM). Genetic diversity analysis showed that, in general, the clustering of accessions within the subpopulations was in accordance with the pedigree information. GWAS performed through a multilocus mixed model revealed 23 MTAs, six, three, seven, four and three for soluble solid content, stalk height, stalk number, stalk weight and cane yield traits, respectively. These MTAs may be validated in other populations to support sugarcane breeding programs with introgression of favorable alleles and marker-assisted selection.

show abstract

“…Sugarcane is a major agricultural crop for sugar production over the world [23][24][25]. Globally, about 80% sugar is isolated from this crop and sugarcane thus, becomes the critical bioenergy crop [26].…”

Section: Introductionmentioning

confidence: 99%

Global Transcriptome Changes of Elongating Internode of Sugarcane in Response to Mepiquat Chloride

Chen

Fan

Zhou

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: Mepiquat chloride (DPC) is an extensively used chemical to control internode growth and compact canopies in cultured plants. Previous studies suggested that DPC could inhibit gibberellin biosynthesis in sugarcane. Unfortunately, the molecular mechanism underlying the suppressive effects of DPC on plant growth is still largely unknown. Results: In the present study, we first obtained the high-quality long transcripts from internode of sugarcane by PacBio Sequel System. A total of 72,671 isoforms with N50 as 3,073 were generated. These long isoforms were used for the following RNA-seq as reference. Subsequently, short reads generated from Illumina Hiseq 4000 platform were used for comparing the differentially expressed genes in DPC and control groups. The transcriptome profiling showed the 6 days post DPC treatment had the most significant changed genes. These genes were related to plant hormone signal transduction and biosynthesis of several metabolites, indicating DPC affected multiple pathways beside depressed gibberellin biosynthesis. The network of DPC on the key stage was illustrated by weighted gene co-expression network analysis (WGCNA). Among the constructed 36 modules, the top positive correlated module with stage of 6 day post spraying DPC was sienna3. Stf0 sulphotransferase, cyclin-like F-box and HOX12 were the hub genes in sienna3 that had high correlation with other genes in this module. The qPCR demonstrated the high accuracy of RNA-seq result. Conclusion: Taken together, we demonstrated the key role of these genes in DPC-induced growth inhibition in sugarcane.

show abstract

Genome-wide association mapping identifies markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection

Cited by 42 publications

References 28 publications

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance

Machine learning approaches reveal genomic regions associated with sugarcane brown rust resistance

A genome-wide association study identified loci for yield component traits in sugarcane (Saccharum spp.)

Global Transcriptome Changes of Elongating Internode of Sugarcane in Response to Mepiquat Chloride

Contact Info

Product

Resources

About