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Cotton is an important crop that has made significant gains in production over the last century.Emerging pests such as the reniform nematode have threatened cotton production. The rare African diploid species Gossypium longicalyx is a wild species that has been used as an important source of reniform nematode immunity. While mapping and breeding efforts have made some strides in transferring this immunity to the cultivated polyploid species, the complexities of interploidal transfer combined with substantial linkage drag have inhibited progress in this area. Moreover, this species shares its most recent common ancestor with the cultivated A-genome diploid cottons, thereby providing insight into the evolution of long, spinnable fiber. Here we report a newly generated de novo genome assembly of G. longicalyx.This high-quality genome leveraged a combination of PacBio long-read technology, Hi-C chromatin conformation capture, and BioNano optical mapping to achieve a chromosome level assembly. The utility of the G. longicalyx genome for understanding reniform immunity and fiber evolution is discussed.

BackgroundAlzheimer disease (AD) has substantial genetic, molecular, and cellular heterogeneity associated with its etiology. Much of our current understanding of the main AD molecular events associated with the amyloid hypothesis (APP, PSEN1 and PSEN2) and neuroimmune modulation (TREM2 and MS4A) is based on genetic studies including GWAS. However, the functional genes, downstream transcriptional ramifications, and the cell-type-specific effects of many GWAS loci remain poorly understood. Understanding these effects can point us to the cellular processes involved in AD and uncover potential therapeutic targets.MethodsWe applied a genetic-based approach to our sample selection; our cohort included carriers of AD pathogenic mutations (APP, PSEN1), risk variants in TREM2, and the resilience variant (rs1582763) in the MS4A cluster associated with cerebrospinal fluid (CSF) soluble TREM2 levels. We performed single-nucleus RNA-sequencing (snRNA-seq) of 1,102,459 nuclei from the human parietal cortex of these carriers. Following initial unbiased clustering and cell-type annotation, we performed deep subclustering analysis per cell type to identify unique cellular transcriptional states associated with these genetic variants. We identified differentially expressed genes between cell states and genetic variant carriers/controls, and performed differential cell proportion analyses to determine key differences among these carriers. We analyzed sequencing data from human dorsolateral prefrontal cortex and mouse models to replicate the enrichment of unique cell states in genetic variant carriers. Finally, we leveraged these cell-state differential expression results to link genes in AD GWAS loci to their functional cell types.FindingsWe identified cell-specific expression states influenced by AD genetic factors for neurons and glia. Autosomal dominant AD (ADAD) brains exhibited unique transcriptional states in all cell types. TREM2 variant carrier brains were also enriched for specific microglia and oligodendrocyte subpopulations. Carriers of the resilience MS4A variant were enriched for an altered activated-microglia expression state. We mapped AD GWAS genes to their potential functional cell types, and some, including PLCG2 and SORL1, were expressed in a broader range of brain cell types than previously reported.InterpretationAD pathogenic, risk, or resilience variants are sufficient to alter the transcriptional and cellular landscape of human brains. Overall, our results suggest that the genetic architecture contributes to the cortical cellular heterogeneity associated with disease status, which is a critical factor to consider when designing drug trials and selecting the treatment program for AD patients.Our findings suggest that integrating genetic and single-cell molecular data facilitates our understanding of the heterogeneity of pathways, biological processes and cell types modulated by genetic risk factors for AD.FundingUS National Institutes of Health, Hope Center, Archer foundation, Alzheimer Association, CZI.

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Different species, genes, and locations within genes use different codons to fine-tune gene expression. Within genes, the ramp sequence assists in ribosome spacing and decreases downstream collisions by incorporating slowly-translated codons at the beginning of a gene. Although previously reported as occurring in some species, no previous attempt at extracting the ramp sequence from specific genes has been published. We present ExtRamp, a software package that quickly extracts ramp sequences from any species using the tRNA adaptation index or relative codon adaptiveness. Different filters facilitate the analysis of codon efficiency and enable identification of genes with a ramp sequence. We validate the existence of a ramp sequence in most species by running ExtRamp on 229 742 339 genes across 23 428 species. We evaluate differences in reported ramp sequences when we use different parameters. Using the strictest ramp sequence cut-off, we show that across most taxonomic groups, ramp sequences are approximately 20–40 codons long and occur in about 10% of gene sequences. We also show that in Drosophila melanogaster as gene expression increases, a higher proportion of genes have ramp sequences. We provide a framework for performing this analysis on other species. ExtRamp is freely available at https://github.com/ridgelab/ExtRamp.