Gene processing control loops suggested by sequencing, splicing, and RNA folding

Abstract Background Small RNAs are known to regulate diverse gene expression processes including translation, transcription, and splicing. Among small RNAs, the microRNAs (miRNAs) of 17 to 27 nucleotides (nts) undergo biogeneses including primary transcription, RNA excision and folding, nuclear export, cytoplasmic processing, and then bioactivity as regulatory agents. We propose that analogous hairpins from RNA molecules that function as part of the spliceosome might also be the source of small, regulatory RNAs (somewhat smaller than miRNAs). Results Deep sequencing technology has enabled discovery of a novel 16-nt RNA sequence in total RNA from human brain that we propose is derived from RNU1, an RNA component of spliceosome assembly. Bioinformatic alignments compel inquiring whether the novel 16-nt sequence or its precursor have a regulatory function as well as determining aspects of how processing intersects with the miRNA biogenesis pathway. Specifically, our preliminary in silico investigations reveal the sequence could regulate splicing factor Arg/Ser rich 1 (SFRS1), a gene coding an essential protein component of the spliceosome. All 16-base source sequences in the UCSC Human Genome Browser are within the 14 instances of RNU1 genes listed in wgEncodeGencodeAutoV3. Furthermore, 10 of the 14 instances of the sequence are also within a common 28-nt hairpin-forming subsequence of RNU1. Conclusions An abundant 16-nt RNA sequence is sourced from a spliceosomal RNA, lies in a stem of a predicted RNA hairpin, and includes reverse complements of subsequences of the 3'UTR of a gene coding for a spliceosome protein. Thus RNU1 could function both as a component of spliceosome assembly and as inhibitor of production of the essential, spliceosome protein coded by SFRS1. Beyond this example, a general procedure is needed for systematic discovery of multiple alignments of sequencing, splicing, and RNA folding data

Rubber agroforestry in Thailand provides some biodiversity benefits without reducing yields

Monocultural rubber plantations have replaced tropical forest, causing biodiversity loss. While protecting intact or semi‐intact biodiverse forest is paramount, improving biodiversity value within the 11.4 million hectares of existing rubber plantations could offer important conservation benefits, if yields are also maintained. Some farmers practice agroforestry with high‐yielding clonal rubber varieties to increase and diversify incomes. Here, we ask whether such rubber agroforestry improves biodiversity value or affects rubber yields relative to monoculture. We surveyed birds, fruit‐feeding butterflies and reptiles in 25 monocultural and 39 agroforest smallholder rubber plots in Thailand, the world's biggest rubber producer. Management and vegetation structure data were collected from each plot, and landscape composition around plots was quantified. Rubber yield data were collected for a separate set of 34 monocultural and 47 agroforest rubber plots in the same region. Reported rubber yields did not differ between agroforests and monocultures, meaning adoption of agroforestry in this context should not increase land demand for natural rubber. Butterfly richness was greater in agroforests, where richness increased with greater natural forest extent in the landscape. Bird and reptile richness were similar between agroforests and monocultures, but bird richness increased with the height of herbaceous vegetation inside rubber plots. Species composition of butterflies differed between agroforests and monocultures, and in response to natural forest extent, while bird composition was influenced by herbaceous vegetation height within plots, the density of non‐rubber trees within plots (representing agroforestry complexity) and natural forest extent in the landscape. Reptile composition was influenced by canopy cover and open habitat extent in the landscape. Conservation priority and forest‐dependent birds were not supported within rubber. Synthesis and applications. Rubber agroforestry using clonal varieties provides modest biodiversity benefits relative to monocultures, without compromising yields. Agroforests may also generate ecosystem service and livelihood benefits. Management of monocultural rubber production to increase inter‐row vegetation height and complexity may further benefit biodiversity. However, biodiversity losses from encroachment of rubber onto forests will not be offset by rubber agroforestry or rubber plot management. This evidence is important for developing guidelines around biodiversity‐friendly rubber and sustainable supply chains, and for farmers interested in diversifying rubber production

Massive-Scale RNA-Seq Analysis of Non Ribosomal Transcriptome in Human Trisomy 21

Hybridization- and tag-based technologies have been successfully used in Down syndrome to identify genes involved in various aspects of the pathogenesis. However, these technologies suffer from several limits and drawbacks and, to date, information about rare, even though relevant, RNA species such as long and small non-coding RNAs, is completely missing. Indeed, none of published works has still described the whole transcriptional landscape of Down syndrome. Although the recent advances in high-throughput RNA sequencing have revealed the complexity of transcriptomes, most of them rely on polyA enrichment protocols, able to detect only a small fraction of total RNA content. On the opposite end, massive-scale RNA sequencing on rRNA-depleted samples allows the survey of the complete set of coding and non-coding RNA species, now emerging as novel contributors to pathogenic mechanisms. Hence, in this work we analysed for the first time the complete transcriptome of human trisomic endothelial progenitor cells to an unprecedented level of resolution and sensitivity by RNA-sequencing. Our analysis allowed us to detect differential expression of even low expressed genes crucial for the pathogenesis, to disclose novel regions of active transcription outside yet annotated loci, and to investigate a plethora of non-polyadenilated long as well as short non coding RNAs. Novel splice isoforms for a large subset of crucial genes, and novel extended untranslated regions for known genes—possibly novel miRNA targets or regulatory sites for gene transcription—were also identified in this study. Coupling the rRNA depletion of samples, followed by high-throughput RNA-sequencing, to the easy availability of these cells renders this approach very feasible for transcriptome studies, offering the possibility of investigating in-depth blood-related pathological features of Down syndrome, as well as other genetic disorders

Multi-Platform Next-Generation Sequencing of the Domestic Turkey (Meleagris gallopavo): Genome Assembly and Analysis

The combined application of next-generation sequencing platforms has provided an economical approach to unlocking the potential of the turkey genome

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations

Introducing evolutionary biologists to the analysis of big data: guidelines to organize extended bioinformatics training courses

Research in evolutionary biology has been progressively influenced by big data such as massive genome and transcriptome sequencing data, scalar measurements of several phenotypes on tens to thousands of individuals, as well as from collecting worldwide environmental data at an increasingly detailed scale. The handling and analysis of such data require computational skills that usually exceed the abilities of most traditionally trained evolutionary biologists. Here we discuss the advantages, challenges and considerations for organizing and running bioinformatics training courses of 2–3 weeks in length to introduce evolutionary biologists to the computational analysis of big data. Extended courses have the advantage of offering trainees the opportunity to learn a more comprehensive set of complementary topics and skills and allowing for more time to practice newly acquired competences. Many organizational aspects are common to any course, as the need to define precise learning objectives and the selection of appropriate and highly motivated instructors and trainees, among others. However, other features assume particular importance in extended bioinformatics training courses. To successfully implement a learning-by-doing philosophy, sufficient and enthusiastic teaching assistants (TAs) are necessary to offer prompt help to trainees. Further, a good balance between theoretical background and practice time needs to be provided and assured that the schedule includes enough flexibility for extra review sessions or further discussions if desired. A final project enables trainees to apply their newly learned skills to real data or case studies of their interest. To promote a friendly atmosphere throughout the course and to build a close-knit community after the course, allow time for some scientific discussions and social activities. In addition, to not exhaust trainees and TAs, some leisure time needs to be organized. Finally, all organization should be done while keeping the budget within fair limits. In order to create a sustainable course that constantly improves and adapts to the trainees’ needs, gathering short- and long-term feedback after the end of the course is important. Based on our experience we have collected a set of recommendations to effectively organize and run extended bioinformatics training courses for evolutionary biologists, which we here want to share with the community. They offer a complementary way for the practical teaching of modern evolutionary biology and reaching out to the biological community.Peer reviewe