scRNA-seq Reveals Novel Genetic Pathways and Sex Chromosome Regulation in Tribolium Spermatogenesis.

Spermatogenesis is critical to sexual reproduction yet evolves rapidly in many organisms. High-throughput single-cell transcriptomics promises unparalleled insight into this important process but understanding can be impeded in nonmodel systems by a lack of known genes that can reliably demarcate biologically meaningful cell populations. Tribolium castaneum, the red flour beetle, lacks known markers for spermatogenesis found in insect species like Drosophila melanogaster. Using single-cell sequencing data collected from adult beetle testes, we implement a strategy for elucidating biologically meaningful cell populations by using transient expression stage identification markers, weighted principal component clustering, and SNP-based haploid/diploid phasing. We identify populations that correspond to observable points in sperm differentiation and find species specific markers for each stage. Our results indicate that molecular pathways underlying spermatogenesis in Coleoptera are substantially diverged from those in Diptera. We also show that most genes on the X chromosome experience meiotic sex chromosome inactivation. Temporal expression of Drosophila MSL complex homologs coupled with spatial analysis of potential chromatin entry sites further suggests that the dosage compensation machinery may mediate escape from meiotic sex chromosome inactivation and postmeiotic reactivation of the X chromosome.

Comparison of the Strengths and Weaknesses of Machine Learning Algorithms and Feature Selection on KEGG Database Microbial Gene Pathway Annotation and Its Effects on Reconstructed Network Topology.

The development of tools for the annotation of genes from newly sequenced species has not evolved much from homologous alignment to prior annotated species. While the quality of gene annotations continues to decline as we sequence and assemble more evolutionary distant gut microbiome species, machine learning presents a high quality alternative to traditional techniques. In this study, we investigate the relative performance of common classical and nonclassical machine learning algorithms in the problem of gene annotation using human microbiome-associated species genes from the KEGG database. The majority of the ensemble, clustering, and deep learning algorithms that we investigated showed higher prediction accuracy than CD-Hit in predicting partial KEGG function. Motif-based, machine-learning methods of annotation in new species were faster and had higher precision-recall than methods of homologous alignment or orthologous gene clustering. Gradient boosted ensemble methods and neural networks also predicted higher connectivity in reconstructed KEGG pathways, finding twice as many new pathway interactions than blast alignment. The use of motif-based, machine-learning algorithms in annotation software will allow researchers to develop powerful tools to interact with bacterial microbiomes in ways previously unachievable through homologous sequence alignment alone.

Integrative Analysis of Gene Expression and miRNAs Reveal Biological Pathways Associated with Bud Paradormancy and Endodormancy in Grapevine.

Transition of grapevine buds from paradormancy to endodormancy is coordinated by changes in gene expression, phytohormones, transcription factors, and other molecular regulators, but the mechanisms involved in transcriptional and post-transcriptional regulation of dormancy stages are not well delineated. To identify potential regulatory targets, an integrative analysis of differential gene expression profiles and their inverse relationships with miRNA abundance was performed in paradormant (long day (LD) 15 h) or endodormant (short day (SD), 13 h) Vitis riparia buds. There were 400 up- and 936 downregulated differentially expressed genes in SD relative to LD budsGene set and gene ontology enrichment analysis indicated that hormone signaling and cell cycling genes were downregulated in SD relative to LD buds. miRNA abundance and inverse expression analyses of miRNA target genes indicated increased abundance of miRNAs that negatively regulate genes involved with cell cycle and meristem development in endodormant buds and miRNAs targeting starch metabolism related genes in paradormant buds. Analysis of interactions between abundant miRNAs and transcription factors identified a network with coinciding regulation of cell cycle and epigenetic regulation related genes in SD buds. This network provides evidence for cross regulation occurring between miRNA and transcription factors both upstream and downstream of MYB3R1.

Draft genome of the Native American cold hardy grapevine Vitis riparia Michx. 'Manitoba 37'.

Vitis riparia, a critically important Native American grapevine species, is used globally in rootstock and scion breeding and contributed to the recovery of the French wine industry during the mid-19th century phylloxera epidemic. This species has abiotic and biotic stress tolerance and the largest natural geographic distribution of the North American grapevine species. Here we report an Illumina short-read 369X coverage, draft de novo heterozygous genome sequence of V. riparia Michx. 'Manitoba 37' with the size of ~495 Mb for 69,616 scaffolds and a N50 length of 518,740 bp. Using RNAseq data, 40,019 coding sequences were predicted and annotated. Benchmarking with Universal Single-Copy Orthologs (BUSCO) analysis of predicted gene models found 96% of the complete BUSCOs in this assembly. The assembly continuity and completeness were further validated using V. riparia ESTs, BACs, and three de novo transcriptome assemblies of three different V. riparia genotypes resulting in >98% of respective sequences/transcripts mapping with this assembly. Alignment of the V. riparia assembly and predicted CDS with the latest V. vinifera 'PN40024' CDS and genome assembly showed 99% CDS alignment and a high degree of synteny. An analysis of plant transcription factors indicates a high degree of homology with the V. vinifera transcription factors. QTL mapping to V. riparia 'Manitoba 37' and V. vinifera PN40024 has identified genetic relationships to phenotypic variation between species. This assembly provides reference sequences, gene models for marker development and understanding V. riparia's genetic contributions in grape breeding and research.