RESUMO

Potato (Solanum tuberosum) is an essential crop for food security and is ranked as the third most important crop worldwide for human consumption. The Diacol Capiro cultivar holds the dominant position in Colombian cultivation, primarily catering to the food processing industry. This highly heterozygous, autotetraploid cultivar belongs to the Andigenum group and it stands out for its adaptation to a wide variety of environments spanning altitudes from 1,800 to 3,200 meters above sea level. Here, a chromosome-scale assembly, referred to as DC, is presented for this cultivar. The assembly was generated by combining circular consensus sequencing with proximity ligation Hi-C for the scaffolding and represents 2.369 Gb with 48 pseudochromosomes covering 2,091 Gb and an anchor rate of 88.26%. The reference genome metrics, including an N50 of 50.5 Mb, a BUSCO (Benchmarking Universal Single-Copy Orthologue) score of 99.38%, and an Long Terminal Repeat Assembly Index score of 13.53, collectively signal the achieved high assembly quality. A comprehensive annotation yielded a total of 154,114 genes, and the associated BUSCO score of 95.78% for the annotated sequences attests to their completeness. The number of predicted NLR (Nucleotide-Binding and Leucine-Rich-Repeat genes) was 2107 with a large representation of NBARC (for nucleotide binding domain shared by Apaf-1, certain R gene products, and CED-4) containing domains (99.85%). Further comparative analysis of the proposed annotation-based assembly with high-quality known potato genomes, showed a similar genome metrics with differences in total gene numbers related to the ploidy status. The genome assembly and annotation of DC presented in this study represent a valuable asset for comprehending potato genetics. This resource aids in targeted breeding initiatives and contributes to the creation of enhanced, resilient, and more productive potato varieties, particularly beneficial for countries in Latin America.

Assuntos

RESUMO

The highly diverse Colombian Central Collection (CCC) of cultivated potatoes is the most important source of genetic variation for breeding and the agricultural development of this staple crop in Colombia. Potato is the primary source of income for more than 100.000 farming families in Colombia. However, biotic and abiotic challenges limit crop production. Furthermore, climate change, food security, and malnutrition constraints call for adaptive crop development to be urgently addressed. The clonal CCC of potatoes contains 1,255 accessions - an extensive collection size that limits its optimal assessment and use. Our study evaluated different collection sizes from the whole clonal collection to define the best core collection that captures the total genetic diversity of this unique collection, to support a characterization more cost-effectively. Initially, we genotyped 1,141 accessions from the clonal collection and 20 breeding lines using 3,586 genome-wide polymorphic markers to study CCC's genetic diversity. The analysis of molecular variance confirmed the CCC's diversity with a significant population structure (Phi=0.359; p-value=0.001). Three main genetic pools were identified within this collection (CCC_Group_A, CCC_Group_B1, and CCC_Group_B2), and the commercial varieties were located across the pools. The ploidy level was the main driver of pool identification, followed by a robust representation of accessions from Phureja and Andigenum cultivar groups based on former taxonomic classifications. We also found divergent heterozygosity values within genetic groups, with greater diversity in genetic groups with tetraploids (CCC_Group_B1: 0.37, and CCC_Group_B2: 0.53) than in diploid accessions (CCC_Group_A: 0.14). We subsequently generated one mini-core collection size of 3 percent (39 entries) and three further core collections sizes of 10, 15, and 20 percent (i.e., 129, 194, and 258 entries, respectively) from the total samples genotyped. As our results indicated that genetic diversity was similar across the sampled core collection sizes compared to the main collection, we selected the smallest core collection size of 10 percent. We expect this 10 percent core collection to be an optimal tool for discovering and evaluating functional diversity in the genebank to advance potato breeding and agricultural-related studies. This study also lays the foundations for continued CCC curation by evaluating duplicity and admixing between accessions, completing the digitalization of data, and ploidy determination using chloroplast count.

RESUMO

The global banana industry is threatened by one of the most devastating diseases: Fusarium wilt of banana. Fusarium wilt of banana is caused by the soilborne fungus Fusarium oxysporum f. sp. cubense (Foc), which almost annihilated the banana production in the late 1950s. A new strain of Foc, known as tropical race 4 (TR4), attacks a wide range of banana varieties, including Cavendish clones, which are the source of 99% of banana exports. In 2019, Foc TR4 was reported in Colombia, and more recently (2021) in Peru. In this study, we sequenced three fungal isolates identified as Foc TR4 from La Guajira (Colombia) and compared them against 19 whole-genome sequences of Foc TR4 publicly available, including four genome sequences recently released from Peru. To understand the genetic relatedness of the Colombian Foc TR4 isolates and those from Peru, we conducted a phylogenetic analysis based on a genome-wide set of single nucleotide polymorphisms (SNPs). Additionally, we compared the genomes of the 22 available Foc TR4 isolates, looking for the presence-absence of gene polymorphisms and genomic regions. Our results reveal that (i) the Colombian and Peruvian isolates are genetically distant, which could be better explained by independent incursions of the pathogen to the continent, and (ii) there is a high correspondence between the genetic relatedness and geographic origin of Foc TR4. The profile of present/absent genes and the distribution of missing genomic regions showed a high correspondence to the clades recovered in the phylogenetic analysis, supporting the results obtained by SNP-based phylogeny.

Assuntos

RESUMO

Genotyping-by-sequencing (GBS) is a widely used and cost-effective technique for obtaining large numbers of genetic markers from populations by sequencing regions adjacent to restriction cut sites. Although a standard reference-based pipeline can be followed to analyse GBS reads, a reference genome is still not available for a large number of species. Hence, reference-free approaches are required to generate the genetic variability information that can be obtained from a GBS experiment. Unfortunately, available tools to perform de novo analysis of GBS reads face issues of usability, accuracy and performance. Furthermore, few available tools are suitable for analysing data sets from polyploid species. In this manuscript, we describe a novel algorithm to perform reference-free variant detection and genotyping from GBS reads. Nonexact searches on a dynamic hash table of consensus sequences allow for efficient read clustering and sorting. This algorithm was integrated in the Next Generation Sequencing Experience Platform (NGSEP) to integrate the state-of-the-art variant detector already implemented in this tool. We performed benchmark experiments with three different empirical data sets of plants and animals with different population structures and ploidies, and sequenced with different GBS protocols at different read depths. These experiments show that NGSEP has comparable and in some cases better accuracy and always better computational efficiency compared to existing solutions. We expect that this new development will be useful for many research groups conducting population genetic studies in a wide variety of species.

Assuntos

RESUMO

Grafting is typically utilized to merge adapted seedling rootstocks with highly productive clonal scions. This process implies the interaction of multiple genomes to produce a unique tree phenotype. However, the interconnection of both genotypes obscures individual contributions to phenotypic variation (rootstock-mediated heritability), hampering tree breeding. Therefore, our goal was to quantify the inheritance of seedling rootstock effects on scion traits using avocado (Persea americana Mill.) cv. Hass as a model fruit tree. We characterized 240 diverse rootstocks from 8 avocado cv. Hass orchards with similar management in three regions of the province of Antioquia, northwest Andes of Colombia, using 13 microsatellite markers simple sequence repeats (SSRs). Parallel to this, we recorded 20 phenotypic traits (including morphological, biomass/reproductive, and fruit yield and quality traits) in the scions for 3 years (2015-2017). Relatedness among rootstocks was inferred through the genetic markers and inputted in a "genetic prediction" model to calculate narrow-sense heritabilities (h 2) on scion traits. We used three different randomization tests to highlight traits with consistently significant heritability estimates. This strategy allowed us to capture five traits with significant heritability values that ranged from 0.33 to 0.45 and model fits (r) that oscillated between 0.58 and 0.73 across orchards. The results showed significance in the rootstock effects for four complex harvest and quality traits (i.e., total number of fruits, number of fruits with exportation quality, and number of fruits discarded because of low weight or thrips damage), whereas the only morphological trait that had a significant heritability value was overall trunk height (an emergent property of the rootstock-scion interaction). These findings suggest the inheritance of rootstock effects, beyond root phenotype, on a surprisingly wide spectrum of scion traits in "Hass" avocado. They also reinforce the utility of polymorphic SSRs for relatedness reconstruction and genetic prediction of complex traits. This research is, up to date, the most cohesive evidence of narrow-sense inheritance of rootstock effects in a tropical fruit tree crop. Ultimately, our work highlights the importance of considering the rootstock-scion interaction to broaden the genetic basis of fruit tree breeding programs while enhancing our understanding of the consequences of grafting.

RESUMO

RNA-binding proteins (RBPs) are at the core of post-transcriptional regulation and thus of gene expression control at the RNA level. One of the principal challenges in the field of gene expression regulation is to understand RBPs mechanism of action. As a result of recent evolution of experimental techniques, it is now possible to obtain the RNA regions recognized by RBPs on a transcriptome-wide scale. In fact, CLIP-seq protocols use the joint action of CLIP, crosslinking immunoprecipitation, and high-throughput sequencing to recover the transcriptome-wide set of interaction regions for a particular protein. Nevertheless, computational methods are necessary to process CLIP-seq experimental data and are a key to advancement in the understanding of gene regulatory mechanisms. Considering the importance of computational methods in this area, we present a review of the current status of computational approaches used and proposed for CLIP-seq data.

RESUMO

Nearly two decades have passed since the publication of the first study reporting the discovery of microRNAs (miRNAs). The key role of miRNAs in post-transcriptional gene regulation led to the performance of an increasing number of studies focusing on origins, mechanisms of action and functionality of miRNAs. In order to associate each miRNA to a specific functionality it is essential to unveil the rules that govern miRNA action. Despite the fact that there has been significant improvement exposing structural characteristics of the miRNA-mRNA interaction, the entire physical mechanism is not yet fully understood. In this respect, the development of computational algorithms for miRNA target prediction becomes increasingly important. This manuscript summarizes the research done on miRNA target prediction. It describes the experimental data currently available and used in the field and presents three lines of computational approaches for target prediction. Finally, the authors put forward a number of considerations regarding current challenges and future directions.

Assuntos