The promise and deceit of genomic selection component analyses

Selection component analyses (SCA) relate individual genotype to fitness components such as viability, fecundity and mating success. SCA are based on population genetic models and yield selection estimates directly in terms of predicted allele frequency change. This paper explores the statistical properties of gSCA: experiments that apply SCA to genome-wide scoring of SNPs in field sampled individuals. Computer simulations indicate that gSCA involving a few thousand genotyped samples can detect allele frequency changes of the magnitude that has been documented in field experiments on diverse taxa. To detect selection, imprecise genotyping from low-level sequencing of large samples of individuals provides much greater power than precise genotyping of smaller samples. The simulations also demonstrate the efficacy of ‘haplotype matching’, a method to combine information from a limited collection of whole genome sequence (the reference panel) with the much larger sample of field individuals that are measured for fitness. Pooled sequencing is demonstrated as another way to increase statistical power. Finally, I discuss the interpretation of selection estimates in relation to the Beavis effect, the overestimation of selection intensities at significant loci.

Pooled Sequencing Analysis of Geese (Anser cygnoides) Reveals Genomic Variations Associated With Feather Color

During the domestication of the goose a change in its feather color took place, however, the molecular mechanisms responsible for this change are not completely understood. Here, we performed whole-genome resequencing on three pooled samples of geese (feral and domestic geese), with two distinct feather colors, to identify genes that might regulate feather color. We identified around 8 million SNPs within each of the three pools and validated allele frequencies for a subset of these SNPs using PCR and Sanger sequencing. Several genomic regions with signatures of differential selection were found when we compared the gray and white feather color populations using the FST and Hp approaches. When we combined previous functional studies with our genomic analyses we identified 26 genes (KITLG, MITF, TYRO3, KIT, AP3B1, SMARCA2, ROR2, CSNK1G3, CCDC112, VAMP7, SLC16A2, LOC106047519, RLIM, KIAA2022, ST8SIA4, LOC106044163, TRPM6, TICAM2, LOC106038556, LOC106038575, LOC106038574, LOC106038594, LOC106038573, LOC106038604, LOC106047489, and LOC106047492) that potentially regulate feather color in geese. These results substantially expand the catalog of potential feather color regulators in geese and provide a basis for further studies on domestication and avian feather coloration.

Microarthropod contributions to fitness variation in the common moss Ceratodon purpureus

The evolution of sustained plant–animal interactions depends critically upon genetic variation in the fitness benefits from the interaction. Genetic analyses of such interactions are limited to a few model systems, in part because genetic variation may be absent or the interacting species may be experimentally intractable. Here, we examine the role of sperm-dispersing microarthropods in shaping reproduction and genetic variation in mosses. We established experimental mesocosms with known moss genotypes and inferred the parents of progeny from mesocosms with and without microarthropods, using a pooled sequencing approach. Moss reproductive rates increased fivefold in the presence of microarthropods, relative to control mesocosms. Furthermore, the presence of microarthropods increased the total number of reproducing moss genotypes, and changed the rank-order of fitness of male and female moss genotypes. Interestingly, the genotypes that reproduced most frequently did not produce sporophytes with the most spores, highlighting the challenge of defining fitness in mosses. These results demonstrate that microarthropods provide a fitness benefit for mosses, and highlight the potential for biotic dispersal agents to alter fitness among moss genotypes.

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.

CiBER-seq dissects genetic networks by quantitative CRISPRi profiling of expression phenotypes

To realize the promise of CRISPR-Cas9–based genetics, approaches are needed to quantify a specific, molecular phenotype across genome-wide libraries of genetic perturbations. We addressed this challenge by profiling transcriptional, translational, and posttranslational reporters using CRISPR interference (CRISPRi) with barcoded expression reporter sequencing (CiBER-seq). Our barcoding approach allowed us to connect an entire library of guides to their individual phenotypic consequences using pooled sequencing. CiBER-seq profiling fully recapitulated the integrated stress response (ISR) pathway in yeast. Genetic perturbations causing uncharged transfer RNA (tRNA) accumulation activated ISR reporter transcription. Notably, tRNA insufficiency also activated the reporter, independent of the uncharged tRNA sensor. By uncovering alternate triggers for ISR activation, we illustrate how precise, comprehensive CiBER-seq profiling provides a powerful and broadly applicable tool for dissecting genetic networks.

Defense Response in Brazilian Honey Bees (Apis mellifera scutellata × spp.) Is Underpinned by Complex Patterns of Admixture

In 1957, an invasive and highly defensive honey bee began to spread across Brazil. In the previous year, Brazilian researchers hoped to produce a subtropical-adapted honey bee by crossing local commercial honey bees (of European origin) with a South African honey bee subspecies (Apis mellifera scutellata; an A-lineage honey bee subspecies). The resulting cross—African hybrid honey bees (AHBs)—escaped from their enclosure and spread through the Americas. Today, AHB is the most common honey bee from Northern Argentina to the Southern United States. AHBs are much more likely to sting nest intruders than managed European-derived honey bee colonies. Previous studies have explored how genetic variation contributes to differences in defense response between European-derived honey bee and AHB. Although this work demonstrated very strong genetic effects on defense response, they have yet to pinpoint which genes influence variation in defense response within AHBs, specifically. We quantified defense response for 116 colonies in Brazil and performed pooled sequencing on the most phenotypically divergent samples. We identified 65 loci containing 322 genes that were significantly associated with defense response. Loci were strongly associated with metabolic function, consistent with previous functional genomic analyses of this phenotype. Additionally, defense-associated loci had nonrandom and unexpected patterns of admixture. Defense response was not simply the product of more A-lineage honey bee ancestry as previously assumed, but rather an interaction between A-lineage and European alleles. Our results suggest that a combination of A-lineage and European alleles play roles in defensive behavior in AHBs.

Expression of DAZL Gene in Selected Tissues and Association of Its Polymorphisms with Testicular Size in Hu Sheep

The deleted in azoospermia-like (DAZL) gene encoding an RNA binding protein is pivotal in gametogenesis in lots of species and also acts as a pre-meiosis marker. The current study was conducted to detect expression profiles and single nucleotide polymorphisms (SNPs) of DAZL in sheep using qPCR, DNA-pooled sequencing, improved multiplex ligase detection reaction (iMLDR®) and restriction fragment length polymorphism (RFLP) methods. The results confirmed that ovine DAZL showed the highest expression level at six-months of age across five developmental stage. At six-month stage, DAZL expressed primarily in testis across seven tissues analyzed. The abundance of DAZL in the large-testis group is higher than that in the small-testis group although it is not significant. In addition, six SNPs (SNP1-SNP6) were identified in DAZL. Of those, SNP1 (p < 0.05) and SNP6 (p < 0.01) were significantly correlated with the variation coefficient between left and right epididymis weight (VCTW). The current study implies DAZL may play important roles in testicular development and its SNPs are associated with testicular parameters, which supply important indicators for ram selection at early stage.

CiBER-seq dissects genetic networks by quantitative CRISPRi profiling of expression phenotypes

To realize the promise of CRISPR/Cas9-based genetics, approaches are needed to quantify a specific, molecular phenotype across genome-wide libraries of genetic perturbations. We address this challenge by profiling transcriptional, translational, and post-translational reporters using CRISPR interference with barcoded expression reporter sequencing (CiBER-seq). Our barcoding approach connects an entire library of guides to their individual phenotypic consequences using pooled sequencing. We show that CiBER-seq profiling fully recapitulates the integrated stress response (ISR) pathway in yeast. Genetic perturbations causing uncharged tRNA accumulation activated ISR reporter transcription. Surprisingly, tRNA insufficiency also activated the reporter, independent of the Gcn2 kinase that senses uncharged tRNAs. By uncovering alternate triggers for ISR activation, we illustrate how precise, comprehensive CiBER-seq profiling provides a powerful and broadly applicable tool for dissecting genetic networks.