Single-cell RNA-Sequencing (scRNA-Seq) has become the most widely used high-throughput method for transcription profiling of individual cells. Systematic errors, including batch effects, have been widely reported as a major challenge in high-throughput technologies. Surprisingly, these issues have received minimal attention in published studies based on scRNA-Seq technology. We examined data from five published studies and found that systematic errors can explain a substantial percentage of observed cell-to-cell expression variability. Specifically, we found that the proportion of genes reported as expressed explains a substantial part of observed variability and that this quantity varies systematically across experimental batches. Furthermore, we found that the implemented experimental designs confounded outcomes of interest with batch effects, a design that can bring into question some of the conclusions of these studies. Finally, we propose a simple experimental design that can ameliorate the effect of theses systematic errors have on downstream results.

Variation is the spice of life or, in the case of evolution, variation is the necessary material on which selection can act to enable adaptation. Karyotypic variation in ploidy (the number of homologous chromosome sets) and aneuploidy (imbalance in the number of chromosomes) are fundamentally different than other types of genomic variants. Karyotypic variation emerges through different molecular mechanisms than other mutational events, and unlike mutations that alter the genome at the base pair level, rapid reversion to the wild type chromosome number is often possible. Although karyotypic variation has long been noted and discussed by biologists, interest in the importance of karyotypic variants in evolutionary processes has spiked in recent years, and much remains to be discovered about how karyotypic variants are produced and subsequently selected.

The genetic diversity within a single tumor can be extremely large, possibly with mutations at all coding sites (Ling et al. 2015). In this study, we analyzed 12 cases of multiple hepatocellular carcinoma (HCC) tumors by sequencing and genotyping several samples from each case. In 10 cases, tumors are clonally related by a process of cell migration and colonization. They permit a detailed analysis of the evolutionary forces (mutation, migration, drift and natural selection) that influence the genetic diversity both within and between tumors. In 23 inter-tumor comparisons, the descendant tumor usually shows a higher growth rate than the parent tumor. In contrast, neutral diversity dominates within-tumor observations such that adaptively growing clones are rarely found. The apparent adaptive evolution between tumors can be explained by the inherent bias for detecting larger tumors that have a growth advantage. Beyond these tumors are a far larger number of clones which, growing at a neutral rate and too small to see, can nevertheless be verified by molecular means. Given that the estimated genetic diversity is often very large, therapeutic strategies need to take into account the pre-existence of many drug-resistance mutations. Importantly, these mutations are expected to be in the very low frequency range in the primary tumors (and become frequent in the relapses, as is indeed reported (1-3). In conclusion, tumors may often harbor a very large number of mutations in the very low frequency range. This duality provides both a challenge and an opportunity for designing strategies against drug resistance (4-8).

Annelida represents a large and morphologically diverse group of bilaterian organisms. The recently published polychaete and leech genome sequences revealed an equally dynamic range of diversity at the genomic level. The availability of more annelid genomes will allow for the identification of evolutionary genomic events that helped shape the annelid lineage and better understand the diversity within the group. We sequenced and assembled the genome of the common earthworm, Eisenia fetida. As a first pass at understanding the diversity within the group, we classified 440 earthworm homeoboxes and compared them to those of the leech Helobdella robusta and the polychaete Capitella teleta. We inferred many gene expansions occurring in the lineage connecting the most recent common ancestor (MRCA) of Capitella and Eisenia to the Eisenia/Helobdella MRCA. Likewise, the lineage leading from the Eisenia/Helobdella MRCA to the leech Helobdella robusta has experienced substantial gains and losses. However, the lineage leading from Eisenia/Helobdella MRCA to E. fetida is characterized by extraordinary levels of homeobox gain. The evolutionary dynamics observed in the homeoboxes of these lineages are very likely to be generalizable to all genes. These genome expansions and losses have likely contributed to the remarkable biology exhibited in this group. These results provide a new perspective from which to understand the diversity within these lineages, show the utility of sub-draft genome assemblies for understanding genomic evolution, and provide a critical resource from which the biology of these animals can be studied. The genome data can be accessed through the Eisenia fetida Genome Portal: http://ryanlab.whitney.ufl.edu/genomes/Efet/

Ubiquitination is an essential post-translational regulatory process that can control protein stability, localization, and activity. Ubiquitin is essential for eukaryotic life and is highly conserved, varying in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies in S. cerevisiae indicate that ubiquitin is highly tolerant to single amino acid mutations. To resolve this paradox, we hypothesized that the set of tolerated substitutions would be reduced when the cultures are not grown in rich media conditions and that chemically induced physiologic perturbations might unmask constraints on the ubiquitin sequence. To test this hypothesis, a class of first year UCSF graduate students employed a deep mutational scanning procedure to determine the fitness landscape of a library of all possible single amino acid mutations of ubiquitin in the presence of one of five small molecule perturbations: MG132, Dithiothreitol (DTT), Hydroxyurea (HU), Caffeine, and DMSO. Our data reveal that the number of tolerated substitutions is greatly reduced by DTT, HU, or Caffeine, and that these perturbations uncover “shared sensitized positions” localized to areas around the hydrophobic patch and to the C-terminus. We also show perturbation specific effects including the sensitization of His68 in HU and tolerance to mutation at Lys63 in DTT. Taken together, our data suggest that chemical stress reduces buffering effects in the ubiquitin proteasome system, revealing previously hidden fitness defects. By expanding the set of chemical perturbations assayed, potentially by other classroom-based experiences, we will be able to further address the apparent dichotomy between the extreme sequence conservation and the experimentally observed mutational tolerance of ubiquitin. Finally, this study demonstrates the realized potential of a project lab-based interdisciplinary graduate curriculum.

Pseudomonas syringae pv. phaseolicola (Pph) is a significant bacterial pathogen of agricultural crops, and phage φ6 and other members of the dsRNA virus family Cystoviridae undergo lytic (virulent) infection of Pph, using the type IV pilus as the initial site of cellular attachment. Despite the popularity of Pph/phage φ6 as a model system in evolutionary biology, Pph resistance to phage φ6 remains poorly characterized. To investigate differences between phage φ6 resistant Pph strains, we examined genomic and gene expression variation among three bacterial genotypes that differ in the number of type IV pili expressed per cell: ordinary (wild-type), non-piliated, and super-piliated. Genome sequencing of non-piliated and super-piliated Pph identified few mutations that separate these genotypes from wild type Pph – and none present in genes known to be directly involved in type IV pilus expression. Expression analysis revealed that 81.1% of GO terms up-regulated in the non-piliated strain were down-regulated in the super-piliated strain. This differential expression is particularly prevalent in genes associated with respiration — specifically genes in the tricarboxylic acid cycle (TCA) cycle, aerobic respiration, and acetyl-CoA metabolism. The expression patterns of the TCA pathway appear to be generally up and down-regulated, in non-piliated and super-piliated Pph respectively. As pilus retraction is mediated by an ATP motor, loss of retraction ability might lead to a lower energy draw on the bacterial cell, leading to a different energy balance than wild type. The lower metabolic rate of the super-piliated strain is potentially a result of its loss of ability to retract.

Background Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set. Results We show that unbiased estimates of relatedness can be obtained by using only those SNPs with genotype calls in both individuals. The expected value of this estimator is independent of the SNP depth in each individual, under a model of genotype calling that includes the special case of the two alleles being read at random. In contrast, the estimator of self-relatedness does depend on the SNP depth, and we provide a modification to provide unbiased estimates of self-relatedness. We refer to these methods of estimation as kinship using GBS with depth adjustment (KGD). The estimators can be calculated using matrix methods, which allow efficient computation. Simulation results were consistent with the methods being unbiased, and suggest that the optimal sequencing depth is around 2-4 for relatedness between individuals and 5-10 for self-relatedness. Application to a real data set revealed that some SNP filtering may still be necessary, for the exclusion of SNPs which did not behave in a Mendelian fashion. A simple graphical method (a ‘fin plot’) is given to illustrate this issue and to guide filtering parameters. Conclusion We provide a method which gives unbiased estimates of relatedness, based on SNPs assayed by GBS, which accounts for the depth (including zero depth) of the genotype calls. This allows GBS to be applied at read depths which can be chosen to optimise the information obtained. SNPs with excess heterozygosity, often due to (partial) polyploidy or other duplications can be filtered based on a simple graphical method.