Sampling strategies for sugarcane using either clonal replicates or diverse genotypes can bias the conclusions of RNA-Seq studies.

A key procedure for ensuring statistical confidence in differential gene expression analyses is to use biological replicates to compare distinct groups. Biological replicates allow the estimation of the residual variation in the gene expression levels among samples of a given experimental condition. In sugarcane, it is possible to obtain an estimate of residual variability at two levels: among samples of distinct genotypes of the same experimental treatment, or clonal replicates of the same genotype. The sequencing costs are often a limitation to leveraging both these levels in the same study, stressing the relevance of efforts to determine an appropriate experimental design. We aim to investigate this question by comparing the transcriptional profiles of young sugarcane culms with different sucrose levels using both sampling strategies. Our results show that clonal replicates provided enough statistical power to identify nearly three times more deferentially expressed genes than the more diverse strategy. However, it resulted in potentially less meaningful biological results, because many of the significant genes were likely related to the particular genotype of choice, rather than representing a common expression profile for the compared groups. This study supports the development of sound experimental designs in new studies regarding differential expression for sugarcane.

The Long Read Transcriptome of Rice (Oryza sativa ssp. japonica var. Nipponbare) Reveals Novel Transcripts.

BACKGROUND: High-throughput next-generation sequencing technologies offer a powerful approach to characterizing the transcriptomes of plants. Long read sequencing has been shown to support the discovery of novel isoforms of transcripts. This approach enables the generation of full-length sequences revealing splice variants that may be important in regulating gene action. Investigation of the diversity of transcripts in the rice transcriptome including splice variants was conducted using PacBio long-read sequence data to improve the annotation of the rice genome. RESULTS: A cDNA library was prepared from RNA extracted from leaves, roots, seeds, inflorescences, and panicles of O. sativa ssp. japonica var Nipponbare and sequenced on a PacBio Sequel platform. This produced 346,190 non-redundant full-length non-chimeric reads (FLNC) resulting in 33,504 high-quality transcripts. Half of the transcripts were multi-exonic and entirely matched with the reference transcripts. However, 14,874 novel isoforms were also identified resulting predominantly from intron retention and at least one novel splice site. Intron retention was the prevalent alternative splicing event and exon skipping was the least observed. Of 73,659 splice junctions, 12,755 (17%) represented novel splice junctions with canonical and non-canonical intron boundaries. The complexity of the transcriptome was examined in detail for 19 starch synthesis-related genes, defining 276 spliced isoforms of which 94 splice variants were novel. CONCLUSION: The data reveal the great complexity of the rice transcriptome. The novel transcripts provide new insights that may be a key input in future research to improve the annotation of the rice genome.

Limited allele-specific gene expression in highly polyploid sugarcane.

Polyploidy is widespread in plants, allowing the different copies of genes to be expressed differently in a tissue-specific or developmentally specific way. This allele-specific expression (ASE) has been widely reported, but the proportion and nature of genes showing this characteristic have not been well defined. We now report an analysis of the frequency and patterns of ASE at the whole-genome level in the highly polyploid sugarcane genome. Very high depth whole-genome sequencing and RNA sequencing revealed strong correlations between allelic proportions in the genome and in expressed sequences. This level of sequencing allowed discrimination of each of the possible allele doses in this 12-ploid genome. Most genes were expressed in direct proportion to the frequency of the allele in the genome with examples of polymorphisms being found with every possible discrete level of dose from 1:11 for single-copy alleles to 12:0 for monomorphic sites. The rarer cases of ASE were more frequent in the expression of defense-response genes, as well as in some processes related to the biosynthesis of cell walls. ASE was more common in genes with variants that resulted in significant disruption of function. The low level of ASE may reflect the recent origin of polyploid hybrid sugarcane. Much of the ASE present can be attributed to strong selection for resistance to diseases in both nature and domestication.

Temporal Gene Expression in Apical Culms Shows Early Changes in Cell Wall Biosynthesis Genes in Sugarcane.

Multiple genes in sugarcane control sucrose accumulation and the biosynthesis of cell wall components; however, it is unclear how these genes are expressed in its apical culms. To better understand this process, we sequenced mRNA from +1 stem internodes collected from four genotypes with different concentrations of soluble solids. Culms were collected at four different time points, ranging from six to 12-month-old plants. Here we show differentially expressed genes related to sucrose metabolism and cell wall biosynthesis, including genes encoding invertases, sucrose synthase and cellulose synthase. Our results showed increased expression of invertases in IN84-58, the genotype with lower sugar and higher fiber content, as well as delayed expression of secondary cell wall-related cellulose synthase for the other genotypes. Interestingly, genes involved with hormone metabolism were differentially expressed across time points in the three genotypes with higher soluble solids content. A similar result was observed for genes controlling maturation and transition to reproductive stages, possibly a result of selection against flowering in sugarcane breeding programs. These results indicate that carbon partitioning in apical culms of contrasting genotypes is mainly associated with differential cell wall biosynthesis, and may include early modifications for subsequent sucrose accumulation. Co-expression network analysis identified transcription factors related to growth and development, showing a probable time shift for carbon partitioning occurred in 10-month-old plants.

The experience of teaching introductory programming skills to bioscientists in Brazil.

Computational biology has gained traction as an independent scientific discipline over the last years in South America. However, there is still a growing need for bioscientists, from different backgrounds, with different levels, to acquire programming skills, which could reduce the time from data to insights and bridge communication between life scientists and computer scientists. Python is a programming language extensively used in bioinformatics and data science, which is particularly suitable for beginners. Here, we describe the conception, organization, and implementation of the Brazilian Python Workshop for Biological Data. This workshop has been organized by graduate and undergraduate students and supported, mostly in administrative matters, by experienced faculty members since 2017. The workshop was conceived for teaching bioscientists, mainly students in Brazil, on how to program in a biological context. The goal of this article was to share our experience with the 2020 edition of the workshop in its virtual format due to the Coronavirus Disease 2019 (COVID-19) pandemic and to compare and contrast this year's experience with the previous in-person editions. We described a hands-on and live coding workshop model for teaching introductory Python programming. We also highlighted the adaptations made from in-person to online format in 2020, the participants' assessment of learning progression, and general workshop management. Lastly, we provided a summary and reflections from our personal experiences from the workshops of the last 4 years. Our takeaways included the benefits of the learning from learners' feedback (LLF) that allowed us to improve the workshop in real time, in the short, and likely in the long term. We concluded that the Brazilian Python Workshop for Biological Data is a highly effective workshop model for teaching a programming language that allows bioscientists to go beyond an initial exploration of programming skills for data analysis in the medium to long term.

A Missense Mutation in the MYBPH Gene Is Associated With Abdominal Fat Traits in Meat-Type Chickens.

Chicken is an important source of protein for human nutrition and a model system for growth and developmental biology. Although the genetic architecture of quantitative traits in meat-type chickens has been the subject of ongoing investigation, the identification of mutations associated with carcass traits of economic interest remains challenging. Therefore, our aim was to identify predicted deleterious mutation, which potentially affects protein function, and test if they were associated with carcass traits in chickens. For that, we performed a genome-wide association analysis (GWAS) for breast, thigh and drumstick traits in meat-type chickens and detected 19 unique quantitative trait loci (QTL). We then used: (1) the identified windows; (2) QTL for abdominal fat detected in a previous study with the same population and (3) previously obtained whole genome sequence data, to identify 18 predicted deleterious single nucleotide polymorphisms (SNPs) in those QTL for further association with breast, thigh, drumstick and abdominal fat traits. Using the additive model, a predicted deleterious SNP c.482C > T (SIFT score of 0.4) was associated (p-value < 0.05) with abdominal fat weight and percentage. This SNP is in the second exon of the MYBPH gene, and its allele frequency deviates from Hardy-Weinberg equilibrium. In conclusion, our study provides evidence that the c.482C > T SNP in the MYBPH gene is a putative causal mutation for fat deposition in meat-type chickens.

The Wild Sugarcane and Sorghum Kinomes: Insights Into Expansion, Diversification, and Expression Patterns.

The protein kinase (PK) superfamily is one of the largest superfamilies in plants and the core regulator of cellular signaling. Despite this substantial importance, the kinomes of sugarcane and sorghum have not been profiled. Here, we identified and profiled the complete kinomes of the polyploid Saccharum spontaneum (Ssp) and Sorghum bicolor (Sbi), a close diploid relative. The Sbi kinome was composed of 1,210 PKs; for Ssp, we identified 2,919 PKs when disregarding duplications and allelic copies, and these were related to 1,345 representative gene models. The Ssp and Sbi PKs were grouped into 20 groups and 120 subfamilies and exhibited high compositional similarities and evolutionary divergences. By utilizing the collinearity between the species, this study offers insights into Sbi and Ssp speciation, PK differentiation and selection. We assessed the PK subfamily expression profiles via RNA-Seq and identified significant similarities between Sbi and Ssp. Moreover, coexpression networks allowed inference of a core structure of kinase interactions with specific key elements. This study provides the first categorization of the allelic specificity of a kinome and offers a wide reservoir of molecular and genetic information, thereby enhancing the understanding of Sbi and Ssp PK evolutionary history.

Modern Approaches for Transcriptome Analyses in Plants.

The collection of all transcripts in a cell, a tissue, or an organism is called the transcriptome, or meta-transcriptome when dealing with the transcripts of a community of different organisms. Nowadays, we have a vast array of technologies that allow us to assess the (meta-)transcriptome regarding its composition (which transcripts are produced) and the abundance of its components (what are the expression levels of each transcript), and we can do this across several samples, conditions, and time-points, at costs that are decreasing year after year, allowing experimental designs with ever-increasing complexity. Here we will present the current state of the art regarding the technologies that can be applied to the study of plant transcriptomes and their applications, including differential gene expression and coexpression analyses, identification of sequence polymorphisms, the application of machine learning for the identification of alternative splicing and ncRNAs, and the ranking of candidate genes for downstream studies. We continue with a collection of examples of these approaches in a diverse array of plant species to generate gene/transcript catalogs/atlases, population mapping, identification of genes related to stress phenotypes, and phylogenomics. We finalize the chapter with some of our ideas about the future of this dynamic field in plant physiology.

Differential expression in leaves of Saccharum genotypes contrasting in biomass production provides evidence of genes involved in carbon partitioning.

BACKGROUND: The development of biomass crops aims to meet industrial yield demands, in order to optimize profitability and sustainability. Achieving these goals in an energy crop like sugarcane relies on breeding for sucrose accumulation, fiber content and stalk number. To expand the understanding of the biological pathways related to these traits, we evaluated gene expression of two groups of genotypes contrasting in biomass composition. RESULTS: First visible dewlap leaves were collected from 12 genotypes, six per group, to perform RNA-Seq. We found a high number of differentially expressed genes, showing how hybridization in a complex polyploid system caused extensive modifications in genome functioning. We found evidence that differences in transposition and defense related genes may arise due to the complex nature of the polyploid Saccharum genomes. Genotypes within both biomass groups showed substantial variability in genes involved in photosynthesis. However, most genes coding for photosystem components or those coding for phosphoenolpyruvate carboxylases (PEPCs) were upregulated in the high biomass group. Sucrose synthase (SuSy) coding genes were upregulated in the low biomass group, showing that this enzyme class can be involved with sucrose synthesis in leaves, similarly to sucrose phosphate synthase (SPS) and sucrose phosphate phosphatase (SPP). Genes in pathways related to biosynthesis of cell wall components and expansins coding genes showed low average expression levels and were mostly upregulated in the high biomass group. CONCLUSIONS: Together, these results show differences in carbohydrate synthesis and carbon partitioning in the source tissue of distinct phenotypic groups. Our data from sugarcane leaves revealed how hybridization in a complex polyploid system resulted in noticeably different transcriptomic profiles between contrasting genotypes.

Genomic prediction applied to multiple traits and environments in second season maize hybrids.

Genomic selection has become a reality in plant breeding programs with the reduction in genotyping costs. Especially in maize breeding programs, it emerges as a promising tool for predicting hybrid performance. The dynamics of a commercial breeding program involve the evaluation of several traits simultaneously in a large set of target environments. Therefore, multi-trait multi-environment (MTME) genomic prediction models can leverage these datasets by exploring the correlation between traits and Genotype-by-Environment (G×E) interaction. Herein, we assess predictive abilities of univariate and multivariate genomic prediction models in a maize breeding program. To this end, we used data from 415 maize hybrids evaluated in 4 years of second season field trials for the traits grain yield, number of ears, and grain moisture. Genotypes of these hybrids were inferred in silico based on their parental inbred lines using single nucleotide polymorphisms (SNPs) markers obtained via genotyping-by-sequencing (GBS). Because genotypic information was available for only 257 hybrids, we used the genomic and pedigree relationship matrices to obtain the H matrix for all 415 hybrids. Our results demonstrated that in the single-environment context the use of multi-trait models was always superior in comparison to their univariate counterparts. Besides that, although MTME models were not particularly successful in predicting hybrid performance in untested years, they improved the ability to predict the performance of hybrids that had not been evaluated in any environment. However, the computational requirements of this kind of model could represent a limitation to its practical implementation and further investigation is necessary.

Time-series expression profiling of sugarcane leaves infected with Puccinia kuehnii reveals an ineffective defense system leading to susceptibility.

KEY MESSAGE: Successful orange rust development on sugarcane can potentially be explained as suppression of the plant immune system by the pathogen or delayed plant signaling to trigger defense responses. Puccinia kuehnii is an obligate biotrophic fungus that infects sugarcane leaves causing a disease called orange rust. It spread out to other countries resulting in reduction of crop yield since its first outbreak. One of the knowledge gaps of that pathosystem is to understand the molecular mechanisms altered in susceptible plants by this biotic stress. Here, we investigated the changes in temporal expression of transcripts in pathways associated with the immune system. To achieve this purpose, we used RNA-Seq to analyze infected leaf samples collected at five time points after inoculation. Differential expression analyses of adjacent time points revealed substantial changes at 12, 48 h after inoculation and 12 days after inoculation, coinciding with the events of spore germination, haustoria post-penetration and post-sporulation, respectively. During the first 24 h, a lack of transcripts involved with resistance mechanisms was revealed by underrepresentation of hypersensitive and defense response related genes. However, two days after inoculation, upregulation of genes involved with immune response regulation provided evidence of some potential defense response. Events related to biotic stress responses were predominantly downregulated in the initial time points, but expression was later restored to basal levels. Genes involved in carbohydrate metabolism showed evidence of repression followed by upregulation, possibly to ensure the pathogen nutritional requirements were met. Our results support the hypothesis that P. kuehnii initially suppressed sugarcane genes involved in plant defense systems. Late overexpression of specific regulatory pathways also suggests the possibility of an inefficient recognition system by a susceptible sugarcane genotype.

Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world's leading biomass crop.

BACKGROUND: Sugarcane cultivars are polyploid interspecific hybrids of giant genomes, typically with 10-13 sets of chromosomes from 2 Saccharum species. The ploidy, hybridity, and size of the genome, estimated to have >10 Gb, pose a challenge for sequencing. RESULTS: Here we present a gene space assembly of SP80-3280, including 373,869 putative genes and their potential regulatory regions. The alignment of single-copy genes in diploid grasses to the putative genes indicates that we could resolve 2-6 (up to 15) putative homo(eo)logs that are 99.1% identical within their coding sequences. Dissimilarities increase in their regulatory regions, and gene promoter analysis shows differences in regulatory elements within gene families that are expressed in a species-specific manner. We exemplify these differences for sucrose synthase (SuSy) and phenylalanine ammonia-lyase (PAL), 2 gene families central to carbon partitioning. SP80-3280 has particular regulatory elements involved in sucrose synthesis not found in the ancestor Saccharum spontaneum. PAL regulatory elements are found in co-expressed genes related to fiber synthesis within gene networks defined during plant growth and maturation. Comparison with sorghum reveals predominantly bi-allelic variations in sugarcane, consistent with the formation of 2 "subgenomes" after their divergence ∼3.8-4.6 million years ago and reveals single-nucleotide variants that may underlie their differences. CONCLUSIONS: This assembly represents a large step towards a whole-genome assembly of a commercial sugarcane cultivar. It includes a rich diversity of genes and homo(eo)logous resolution for a representative fraction of the gene space, relevant to improve biomass and food production.

Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world's leading biomass crop

Background: Sugarcane cultivars are polyploid interspecific hybrids of giant genomes, typically with 10–13 sets of chromosomes from 2 Saccharum species. The ploidy, hybridity, and size of the genome, estimated to have >10 Gb, pose a challenge for sequencing. Results: Here we present a gene space assembly of SP80-3280, including 373,869 putative genes and their potential regulatory regions. The alignment of single-copy genes in diploid grasses to the putative genes indicates that we could resolve 2–6 (up to 15) putative homo(eo)logs that are 99.1% identical within their coding sequences. Dissimilarities increase in their regulatory regions, and gene promoter analysis shows differences in regulatory elements within gene families that are expressed in a species-specific manner. We exemplify these differences for sucrose synthase (SuSy) and phenylalanine ammonia-lyase (PAL), 2 gene families central to carbon partitioning. SP80-3280 has particular regulatory elements involved in sucrose synthesis not found in the ancestor Saccharum spontaneum. PAL regulatory elements are found in co-expressed genes related to fiber synthesis within gene networks defined during plant growth and maturation. Comparison with sorghum reveals predominantly bi-allelic variations in sugarcane, consistent with the formation of 2 "subgenomes" after their divergence ~3.8–4.6 million years ago and reveals single-nucleotide variants that may underlie their differences. Conclusions: This assembly represents a large step towards a whole-genome assembly of a commercial sugarcane cultivar. It includes a rich diversity of genes and homo(eo)logous resolution for a representative fraction of the gene space, relevant to improve biomass and food production.

Assembly of the 373k gene space of the polyploid sugarcane genome reveals reservoirs of functional diversity in the world's leading biomass crop

Background: Sugarcane cultivars are polyploid interspecific hybrids of giant genomes, typically with 10–13 sets of chromosomes from 2 Saccharum species. The ploidy, hybridity, and size of the genome, estimated to have >10 Gb, pose a challenge for sequencing. Results: Here we present a gene space assembly of SP80-3280, including 373,869 putative genes and their potential regulatory regions. The alignment of single-copy genes in diploid grasses to the putative genes indicates that we could resolve 2–6 (up to 15) putative homo(eo)logs that are 99.1% identical within their coding sequences. Dissimilarities increase in their regulatory regions, and gene promoter analysis shows differences in regulatory elements within gene families that are expressed in a species-specific manner. We exemplify these differences for sucrose synthase (SuSy) and phenylalanine ammonia-lyase (PAL), 2 gene families central to carbon partitioning. SP80-3280 has particular regulatory elements involved in sucrose synthesis not found in the ancestor Saccharum spontaneum. PAL regulatory elements are found in co-expressed genes related to fiber synthesis within gene networks defined during plant growth and maturation. Comparison with sorghum reveals predominantly bi-allelic variations in sugarcane, consistent with the formation of 2 "subgenomes" after their divergence ~3.8–4.6 million years ago and reveals single-nucleotide variants that may underlie their differences. Conclusions: This assembly represents a large step towards a whole-genome assembly of a commercial sugarcane cultivar. It includes a rich diversity of genes and homo(eo)logous resolution for a representative fraction of the gene space, relevant to improve biomass and food production.

Genomic prediction applied to high-biomass sorghum for bioenergy production.

The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesCπ, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs.

GBS-based single dosage markers for linkage and QTL mapping allow gene mining for yield-related traits in sugarcane.

BACKGROUND: Sugarcane (Saccharum spp.) is predominantly an autopolyploid plant with a variable ploidy level, frequent aneuploidy and a large genome that hampers investigation of its organization. Genetic architecture studies are important for identifying genomic regions associated with traits of interest. However, due to the genetic complexity of sugarcane, the practical applications of genomic tools have been notably delayed in this crop, in contrast to other crops that have already advanced to marker-assisted selection (MAS) and genomic selection. High-throughput next-generation sequencing (NGS) technologies have opened new opportunities for discovering molecular markers, especially single nucleotide polymorphisms (SNPs) and insertion-deletion (indels), at the genome-wide level. The objectives of this study were to (i) establish a pipeline for identifying variants from genotyping-by-sequencing (GBS) data in sugarcane, (ii) construct an integrated genetic map with GBS-based markers plus target region amplification polymorphisms and microsatellites, (iii) detect QTLs related to yield component traits, and (iv) perform annotation of the sequences that originated the associated markers with mapped QTLs to search putative candidate genes. RESULTS: We used four pseudo-references to align the GBS reads. Depending on the reference, from 3,433 to 15,906 high-quality markers were discovered, and half of them segregated as single-dose markers (SDMs) on average. In addition to 7,049 non-redundant SDMs from GBS, 629 gel-based markers were used in a subsequent linkage analysis. Of 7,678 SDMs, 993 were mapped. These markers were distributed throughout 223 linkage groups, which were clustered in 18 homo(eo)logous groups (HGs), with a cumulative map length of 3,682.04 cM and an average marker density of 3.70 cM. We performed QTL mapping of four traits and found seven QTLs. Our results suggest the presence of a stable QTL across locations. Furthermore, QTLs to soluble solid content (BRIX) and fiber content (FIB) traits had markers linked to putative candidate genes. CONCLUSIONS: This study is the first to report the use of GBS for large-scale variant discovery and genotyping of a mapping population in sugarcane, providing several insights regarding the use of NGS data in a polyploid, non-model species. The use of GBS generated a large number of markers and still enabled ploidy and allelic dosage estimation. Moreover, we were able to identify seven QTLs, two of which had great potential for validation and future use for molecular breeding in sugarcane.