Spatio-temporal transcriptome and storage compound profiles of developing faba bean (Vicia faba) seed tissues

Faba bean (Vicia faba) is a legume grown in diverse climate zones with a high potential for increased cultivation and use in food due to its nutritional seeds. In this study, we characterized seed tissue development in faba bean to identify key developmental processes; from embryo expansion at the expense of the endosperm to the maturing storage stages of the bean seed. A spatio-temporal transcriptome profiling analysis, combined with chemical nutrient analysis of protein, starch, and lipid, of endosperm and embryo tissues at different developmental stages, revealed gene expression patterns, transcriptional networks, and biochemical pathways in faba bean. We identified key players in the LAFL (LEC1, ABI3, FUS3, and LEC2) transcription factor network as well as their major repressors VAL1 and ASIL1. Our results showed that proteins accumulated not only in the embryo but also in the endosperm. Starch accumulated throughout seed development and oil content increased during seed development but at very low levels. The patterns of differentially expressed transcripts encoding proteins with functions in the corresponding metabolic pathways for the synthesis of these storage compounds, to a high extent, aligned with these findings. However, the early expression of transcripts encoding WRI1 combined with the late expression of oil body proteins indicated a not manifested high potential for lipid biosynthesis and oil storage. Altogether, this study contributes to increased knowledge regarding seed developmental processes applicable to future breeding methods and seed quality improvement for faba bean.

Comprehensive transcriptome analysis of different potato cultivars provides insight into early blight disease caused by Alternaria solani

BACKGROUND

Early blight, caused by the necrotrophic fungal pathogen Alternaria solani, is an economically important disease affecting the tuber yield worldwide. The disease is mainly controlled by chemical plant protection agents. However, over-using these chemicals can lead to the evolution of resistant A. solani strains and is environmentally hazardous. Identifying genetic disease resistance factors is crucial for the sustainable management of early blight but little effort has been diverted in this direction. Therefore, we carried out transcriptome sequencing of the A. solani interaction with different potato cultivars with varying levels of early blight resistance to identify key host genes and pathways in a cultivar-specific manner.

RESULTS

In this study, we have captured transcriptomes from three different potato cultivars with varying susceptibility to A. solani,  namely Magnum Bonum, Désirée, and Kuras, at 18 and 36 h post-infection. We identified many differentially expressed genes (DEGs) between these cultivars, and the number of DEGs increased with susceptibility and infection time. There were 649 transcripts commonly expressed between the potato cultivars and time points, of which 627 and 22 were up- and down-regulated, respectively. Interestingly, overall the up-regulated DEGs were twice in number as compared to down-regulated ones in all the potato cultivars and time points, except Kuras at 36 h post-inoculation. In general, transcription factor families WRKY, ERF, bHLH, MYB, and C2H2 were highly enriched DEGs, of which a significant number were up-regulated. The majority of the key transcripts involved in the jasmonic acid and ethylene biosynthesis pathways were highly up-regulated. Many transcripts involved in the mevalonate (MVA) pathway, isoprenyl-PP, and terpene biosynthesis were also up-regulated across the potato cultivars and time points. Compared to Magnum Bonum and Désirée, multiple components of the photosynthesis machinery, starch biosynthesis and degradation pathway were down-regulated in the most susceptible potato cultivar, Kuras.

CONCLUSIONS

Transcriptome sequencing identified many differentially expressed genes and pathways, thereby contributing to the improved understanding of the interaction between the potato host and A. solani. The transcription factors identified are attractive targets for genetic modification to improve potato resistance against early blight. The results provide important insights into the molecular events at the early stages of disease development, help to shorten the knowledge gap, and support potato breeding programs for improved early blight disease resistance.

Transcriptional Regulation of Quinoa Seed Quality: Identification of Novel Candidate Genetic Markers for Increased Protein Content

Quinoa (Chenopodium quinoa Willd.) is a crop that has great potential for increased cultivation in diverse climate regions. The seed protein quality obtained from this crop is high concerning the requirements to meet human nutritional needs, but the seed protein content is relatively low if compared to crops such as grain legumes. Increased seed protein content is desirable for increasing the economic viability of this crop in order for it to be used as a protein crop. In this study, we characterized three genotypes of quinoa with different levels of seed protein content. By performing RNA sequencing of developing seeds, we determined the genotype differences in gene expression and identified genetic polymorphisms that could be associated with increased protein content. Storage nutrient analyses of seeds of three quinoa genotypes (Titicaca, Pasankalla, and Regalona) from different ecoregions grown under controlled climate conditions showed that Pasankalla had the highest protein content (20%) and the lowest starch content (46%). Our seed transcriptome analyses revealed highly differentially expressed transcripts (DETs) in Pasankalla as compared to the other genotypes. These DETs encoded functions in sugar transport, starch and protein synthesis, genes regulating embryo size, and seed transcription factors. We selected 60 genes that encode functions in the central carbon metabolism and transcription factors as potential targets for the development of high-precision markers. Genetic polymorphisms, such as single nucleotide polymorphisms (SNPs) and base insertions and deletions (InDels), were found in 19 of the 60 selected genes, which can be further evaluated for the development of genetic markers for high seed protein content in quinoa. Increased cultivation of quinoa can contribute to a more diversified agriculture and support the plant protein diet shift. The identification of quinoa genotypes with contrasting seed quality can help establish a model system that can be used for the identification of precise breeding targets to improve the seed quality of quinoa. The data presented in this study based on nutrient and transcriptome analyses contribute to an enhanced understanding of the genetic regulation of seed quality traits in quinoa and suggest high-precision candidate markers for such traits.

Genome-wide association analysis in dilated cardiomyopathy reveals two new players in systolic heart failure on chromosomes 3p25.1 and 22q11.23

AIMS

Our objective was to better understand the genetic bases of dilated cardiomyopathy (DCM), a leading cause of systolic heart failure.

METHODS AND RESULTS

We conducted the largest genome-wide association study performed so far in DCM, with 2719 cases and 4440 controls in the discovery population. We identified and replicated two new DCM-associated loci on chromosome 3p25.1 [lead single-nucleotide polymorphism (SNP) rs62232870, P = 8.7 × 10-11 and 7.7 × 10-4 in the discovery and replication steps, respectively] and chromosome 22q11.23 (lead SNP rs7284877, P = 3.3 × 10-8 and 1.4 × 10-3 in the discovery and replication steps, respectively), while confirming two previously identified DCM loci on chromosomes 10 and 1, BAG3 and HSPB7. A genetic risk score constructed from the number of risk alleles at these four DCM loci revealed a 3-fold increased risk of DCM for individuals with 8 risk alleles compared to individuals with 5 risk alleles (median of the referral population). In silico annotation and functional 4C-sequencing analyses on iPSC-derived cardiomyocytes identify SLC6A6 as the most likely DCM gene at the 3p25.1 locus. This gene encodes a taurine transporter whose involvement in myocardial dysfunction and DCM is supported by numerous observations in humans and animals. At the 22q11.23 locus, in silico and data mining annotations, and to a lesser extent functional analysis, strongly suggest SMARCB1 as the candidate culprit gene.

CONCLUSION

This study provides a better understanding of the genetic architecture of DCM and sheds light on novel biological pathways underlying heart failure.

Comparison of Morphological and Genetic Characteristics of Avocados Grown in Tanzania

Tanzania has been growing avocado for decades. A wide variability of the avocado germplasm has been found, and the crop is largely contributing to the earnings of the farmers, traders, and the government, but its genetic diversity is scantly investigated. With the purpose of comparing morphological and genetic characteristics of this germplasm and uncovering the correlation between them and the geographical location, 226 adult seedling avocado trees were sampled in southwestern Tanzania. Their morphological characters were recorded, and their genetic diversity was evaluated based on 10 microsatellite loci. Discriminant analysis of principal components showed that the germplasm studied consisted of four genetic clusters that had an overall average gene diversity of 0.59 and 15.9% molecular variation among them. Most of the phenotypes were common in at least two clusters. The genetic clusters were also portrayed by multivariate analysis and hierarchical clustering for the molecular data but not for the morphology data. Using the Mantel test, a weak significant correlation was found between the genetic, morphological, and geographical distances, which indicates that the genetic variation present in the material is weakly reflected by the observed phenotypic variation and that both measures of variation varied slightly with the geographical sampling locations.

QTL Mapping for Domestication-Related Characteristics in Field Cress (Lepidium campestre)-A Novel Oil Crop for the Subarctic Region

Domestication of a new crop requires identification and improvement of desirable characteristics Field cress (Lepidium campestre) is being domesticated as a new oilseed crop, particularly for northern temperate regions.. In the present study, an F₂ mapping population and its F₃ progenies were used to identify quantitative trait loci (QTLs) for plant height (PH), number of stems per plant (NS), stem growth orientation (SO), flowering habit (FH), earliness (ER), seed yield per plant (SY), pod shattering resistance (SHR), and perenniality (PE). A highly significant correlation (p < 0.001) was observed between several pairs of characteristics, including SY and ER (negative) or ER and PE (positive). The inclusive composite interval mapping approach was used for QTL mapping using 2330 single nucleotide polymorphism (SNP) markers mapped across the eight field cress linkage groups. Nine QTLs were identified with NS, PH, SO, and PE having 3, 3, 2, and 1 QTLs, explaining 21.3%, 29.5%, 3.8%, and 7.2% of the phenotypic variation, respectively. Candidate genes behind three of the QTLs and favorable marker alleles for different classes of each characteristic were identified. Following their validation through further study, the identified QTLs and associated favorable marker alleles can be used in marker-aided breeding to speed up the domestication of field cress.

Effect of RNA silencing suppression activity of chrysanthemum virus B p12 protein on small RNA species

Chrysanthemum virus B encodes a multifunctional p12 protein that acts as a transcriptional activator in the nucleus and as a suppressor of RNA silencing in the cytoplasm. Here, we investigated the impact of p12 on accumulation of major classes of small RNAs (sRNAs). The results show dramatic changes in the sRNA profiles characterised by an overall reduction in sRNA accumulation, changes in the pattern of size distribution of canonical siRNAs and in the ratio between sense and antisense strands, lower abundance of siRNAs with a U residue at the 5'-terminus, and changes in the expression of certain miRNAs, most of which were downregulated.

Genetic diversity of avocado from the southern highlands of Tanzania as revealed by microsatellite markers

BACKGROUND

Avocado is an important cash crop in Tanzania, however its genetic diversity is not thoroughly investigated. This study was undertaken to explore the genetic diversity of avocado in the southern highlands using microsatellite markers. A total of 226 local avocado trees originating from seeds were sampled in eight districts of the Mbeya, Njombe and Songwe regions. Each district was considered as a population. The diversity at 10 microsatellite loci was investigated.

RESULTS

A total of 167 alleles were detected across the 10 loci with an average of 16.7 ± 1.3 alleles per locus. The average expected and observed heterozygosity were 0.84 ± 0.02 and 0.65 ± 0.04, respectively. All but two loci showed a significant deviation from the Hardy-Weinberg principle. Analysis of molecular variance showed that about 6% of the variation was partitioned among the eight geographic populations. Population F_ST pairwise comparisons revealed lack of genetic differentiation for the seven of 28 population pairs tested. The principal components analysis (PCA) and hierarchical cluster analysis showed a mixing of avocado trees from different districts. The model-based STRUCTURE subdivided the trees samples into four major genetic clusters.

CONCLUSION

High diversity detected in the analysed avocado germplasm implies that this germplasm is a potentially valuable source of variable alleles that might be harnessed for genetic improvement of this crop in Tanzania. The mixing of avocado trees from different districts observed in the PCA and dendrogram points to strong gene flow among the avocado populations, which led to population admixture revealed in the STRUCTURE analysis. However, there is still significant differentiation among the tree populations from different districts that can be utilized in the avocado breeding program.

MACARON: a python framework to identify and re-annotate multi-base affected codons in whole genome/exome sequence data

Summary

Predicted deleteriousness of coding variants is a frequently used criterion to filter out variants detected in next-generation sequencing projects and to select candidates impacting on the risk of human diseases. Most available dedicated tools implement a base-to-base annotation approach that could be biased in presence of several variants in the same genetic codon. We here proposed the MACARON program that, from a standard VCF file, identifies, re-annotates and predicts the amino acid change resulting from multiple single nucleotide variants (SNVs) within the same genetic codon. Applied to the whole exome dataset of 573 individuals, MACARON identifies 114 situations where multiple SNVs within a genetic codon induce an amino acid change that is different from those predicted by standard single SNV annotation tool. Such events are not uncommon and deserve to be studied in sequencing projects with inconclusive findings.

Availability and implementation

MACARON is written in python with codes available on the GENMED website (www.genmed.fr).

Supplementary information

Supplementary data are available at Bioinformatics online.

Benchmarking the next generation of homology inference tools

Motivation: Over the last decades, vast numbers of sequences were deposited in public databases. Bioinformatics tools allow homology and consequently functional inference for these sequences. New profile-based homology search tools have been introduced, allowing reliable detection of remote homologs, but have not been systematically benchmarked. To provide such a comparison, which can guide bioinformatics workflows, we extend and apply our previously developed benchmark approach to evaluate the ‘next generation’ of profile-based approaches, including CS-BLAST, HHSEARCH and PHMMER, in comparison with the non-profile based search tools NCBI-BLAST, USEARCH, UBLAST and FASTA.

Method: We generated challenging benchmark datasets based on protein domain architectures within either the PFAM + Clan, SCOP/Superfamily or CATH/Gene3D domain definition schemes. From each dataset, homologous and non-homologous protein pairs were aligned using each tool, and standard performance metrics calculated. We further measured congruence of domain architecture assignments in the three domain databases.

Results: CSBLAST and PHMMER had overall highest accuracy. FASTA, UBLAST and USEARCH showed large trade-offs of accuracy for speed optimization.

Conclusion: Profile methods are superior at inferring remote homologs but the difference in accuracy between methods is relatively small. PHMMER and CSBLAST stand out with the highest accuracy, yet still at a reasonable computational cost. Additionally, we show that less than 0.1% of Swiss-Prot protein pairs considered homologous by one database are considered non-homologous by another, implying that these classifications represent equivalent underlying biological phenomena, differing mostly in coverage and granularity.

Availability and Implementation: Benchmark datasets and all scripts are placed at (http://sonnhammer.org/download/Homology_benchmark).

Contact:forslund@embl.de

Supplementary information: Supplementary data are available at Bioinformatics online.