De novo assembly of the olive fruit fly (Bactrocera oleae) genome with linked-reads and long-read technologies minimizes gaps and provides exceptional Y chromosome assembly

Background: The olive fruit fly, Bactrocera oleae, is the most important pest in the olive fruit agribusiness industry. This is because female flies lay their eggs in the unripe fruits and upon hatching the larvae feed on the fruits thus destroying them. The lack of a high-quality genome and other genomic and transcriptomic data has hindered progress in understanding the fly’s biology and proposing alternative control methods to pesticide use. Results: Genomic DNA was sequenced from male and female Demokritos strain flies, maintained in the laboratory for over 45 years. We used short-, mate-pair-, and long-read sequencing technologies to generate a combined male-female genome assembly (GenBank accession GCA_001188975.2). Genomic DNA sequencing from male insects using 10x Genomics linked-reads technology followed by mate-pair and long-read scaffolding and gap-closing generated a highly contiguous 489 Mb genome with a scaffold N50 of 4.69 Mb and L50 of 30 scaffolds (GenBank accession GCA_001188975.4). RNA-seq data generated from 12 tissues and/or developmental stages allowed for genome annotation. Short reads from both males and females and the chromosome quotient method enabled identification of Y-chromosome scaffolds which were extensively validated by PCR. Conclusions: The high-quality genome generated represents a critical tool in olive fruit fly research. We provide an extensive RNA-seq data set, and genome annotation, critical towards gaining an insight into the biology of the olive fruit fly. In addition, elucidation of Y-chromosome sequences will advance our understanding of the Y-chromosome’s organization, function and evolution and is poised to provide avenues for sterile insect technique approaches

Metagenomic analysis of planktonic riverine microbial consortia using nanopore sequencing reveals insight into river microbe taxonomy and function

Background Riverine ecosystems are biogeochemical powerhouses driven largely by microbial communities that inhabit water columns and sediments. Because rivers are used extensively for anthropogenic purposes (drinking water, recreation, agriculture, and industry), it is essential to understand how these activities affect the composition of river microbial consortia. Recent studies have shown that river metagenomes vary considerably, suggesting that microbial community data should be included in broad-scale river ecosystem models. But such ecogenomic studies have not been applied on a broad “aquascape” scale, and few if any have applied the newest nanopore technology. Results We investigated the metagenomes of 11 rivers across 3 continents using MinION nanopore sequencing, a portable platform that could be useful for future global river monitoring. Up to 10 Gb of data per run were generated with average read lengths of 3.4 kb. Diversity and diagnosis of river function potential was accomplished with 0.5–1.0 ⋅ 106 long reads. Our observations for 7 of the 11 rivers conformed to other river-omic findings, and we exposed previously unrecognized microbial biodiversity in the other 4 rivers. Conclusions Deeper understanding that emerged is that river microbial consortia and the ecological functions they fulfil did not align with geographic location but instead implicated ecological responses of microbes to urban and other anthropogenic effects, and that changes in taxa manifested over a very short geographic space

Inferring structural properties of protein-DNA binding using high-throughput sequencing. The paradigm of GATA1, KLF1 and their complexes GATA1/FOG1 and GATA1/KLF1. Insights into the transcriptional regulation of the erythroid cell lineage.

GATA1 and KLF1 are transcription factors that regulate genes which are important for the development of erythroid cells. The GATA1 transcriptional co-factor FOG1 has been shown to be essential in a wide range of GATA1 dependent cellular functions. Here we tried to understand the diverse mechanisms by which GATA1 and KLF1 recognize their binding sites, how the GATA1 recognition mechanisms are affected by complexation with either FOG1 or KLF1 and how the GATA1 recognition mechanisms affect the transcriptional regulation of the erythroid differentiation. We profiled the DNA binding specificities/affinities of a GATA1 fragment (mGATA1NC), that contains only the two DNA binding domains (N-terminal and C-terminal Zn finger), and the DNA binding specificities/affinities of a KLF1 fragment (mKLF1257-358), that contains the three DNA binding domains, using a novel methodology that combines EMSA with high throughput sequencing (EMSA-seq (Wong et al., 2011a)). We also profiled the DNA binding specificities of the C-terminal Zn finger of GATA1 alone (mGATA1C), the wt-mGATA1, the wt-mGATA1/wt-mFOG1 complex and the mGATA1NC/mKLF1257-358 complex. At first, we confirmed that the N-terminal Zn finger of GATA1 has a strong preference for the “GATC” motif, whereas the C-terminal Zn finger of GATA1 has a strong preference for the “GATA” motif. Next, we found that in the mGATA1NC, both DNA binding domains can bind simultaneously a wide range of different positional combinations of the co-occurring "GATA” and “GATC” motifs, on the same DNA sequence. The wt-mGATA1 did not show the ability to bind in the same co-occurring motifs implying an effect of the non-DNA binding domains of the protein in the regulation of its DNA binding specificities. On the contrary, complexation of wt-mGATA1 with the wt-mFOG1 partially restored its ability to bind in a now limited range of different positional combinations of the co-occurring “GATA” and “GATC” motifs, on the same DNA sequence. Similar observations were made for other pairs of GATA1 N-terminal and C-terminal Zn finger specific motifs. We then projected the GATA1 DNA binding specificities/affinities in vivo and we classified the GATA1 ChIP-seq peaks in low, medium or high affinity based on the number of the GATA1 motifs. We noticed that high affinity GATA1 ChIP-seq peaks tend to appear in regions with low nucleosome occupancy. We also noticed that GATA1 ChIP-seq peaks in the enhancer regions are usually high affinity whereas GATA1 ChIP-seq peaks in the proximal promoter regions are usually low affinity. Additionally, we observed that high affinity GATA1 ChIP-seq peaks are usually found in regions with increased levels of H3K4me2 and are associated with a higher decrease in the H3K4me3 levels on the TSS of the nearby genes. None of these GATA1 related in vivo observations were found for the KLF1 ChIP-seq positions. These findings significantly advance our understanding of the DNA binding properties of GATA1, KLF1 and their complexes and give an insight on the importance of the GATA1 DNA binding affinities in the regulation of the erythroid transcriptional program. Overall the work establishes an experimental and analytical framework to investigate how transcriptional co-factors can change the DNA binding specificities of specific transcription factors and how integration of the transcription factor DNA binding affinities with in vivo data can give novel insights into the transcriptional regulation.</p

Inferring structural properties of protein-DNA binding using high-throughput sequencing. The paradigm of GATA1, KLF1 and their complexes GATA1/FOG1 and GATA1/KLF1. Insights into the transcriptional regulation of the erythroid cell lineage.

GATA1 and KLF1 are transcription factors that regulate genes which are important for the development of erythroid cells. The GATA1 transcriptional co-factor FOG1 has been shown to be essential in a wide range of GATA1 dependent cellular functions. Here we tried to understand the diverse mechanisms by which GATA1 and KLF1 recognize their binding sites, how the GATA1 recognition mechanisms are affected by complexation with either FOG1 or KLF1 and how the GATA1 recognition mechanisms affect the transcriptional regulation of the erythroid differentiation. We profiled the DNA binding specificities/affinities of a GATA1 fragment (mGATA1NC), that contains only the two DNA binding domains (N-terminal and C-terminal Zn finger), and the DNA binding specificities/affinities of a KLF1 fragment (mKLF1257-358), that contains the three DNA binding domains, using a novel methodology that combines EMSA with high throughput sequencing (EMSA-seq (Wong et al., 2011a)). We also profiled the DNA binding specificities of the C-terminal Zn finger of GATA1 alone (mGATA1C), the wt-mGATA1, the wt-mGATA1/wt-mFOG1 complex and the mGATA1NC/mKLF1257-358 complex. At first, we confirmed that the N-terminal Zn finger of GATA1 has a strong preference for the “GATC” motif, whereas the C-terminal Zn finger of GATA1 has a strong preference for the “GATA” motif. Next, we found that in the mGATA1NC, both DNA binding domains can bind simultaneously a wide range of different positional combinations of the co-occurring “GATA” and “GATC” motifs, on the same DNA sequence. The wt-mGATA1 did not show the ability to bind in the same co-occurring motifs implying an effect of the non-DNA binding domains of the protein in the regulation of its DNA binding specificities. On the contrary, complexation of wt-mGATA1 with the wt-mFOG1 partially restored its ability to bind in a now limited range of different positional combinations of the co-occurring “GATA” and “GATC” motifs, on the same DNA sequence. Similar observations were made for other pairs of GATA1 N-terminal and C-terminal Zn finger specific motifs. We then projected the GATA1 DNA binding specificities/affinities in vivo and we classified the GATA1 ChIP-seq peaks in low, medium or high affinity based on the number of the GATA1 motifs. We noticed that high affinity GATA1 ChIP-seq peaks tend to appear in regions with low nucleosome occupancy. We also noticed that GATA1 ChIP-seq peaks in the enhancer regions are usually high affinity whereas GATA1 ChIP-seq peaks in the proximal promoter regions are usually low affinity. Additionally, we observed that high affinity GATA1 ChIP-seq peaks are usually found in regions with increased levels of H3K4me2 and are associated with a higher decrease in the H3K4me3 levels on the TSS of the nearby genes. None of these GATA1 related in vivo observations were found for the KLF1 ChIP-seq positions. These findings significantly advance our understanding of the DNA binding properties of GATA1, KLF1 and their complexes and give an insight on the importance of the GATA1 DNA binding affinities in the regulation of the erythroid transcriptional program. Overall the work establishes an experimental and analytical framework to investigate how transcriptional co-factors can change the DNA binding specificities of specific transcription factors and how integration of the transcription factor DNA binding affinities with in vivo data can give novel insights into the transcriptional regulation.This thesis is not currently available in ORA