Biology subjects

Schaffer, A. A.

Publications and source records attributed to Schaffer, A. A..

25 records · Page 2Linked to original sources

bioRxiv2021

Underground Heterosis for Melons Yield

Heterosis, the superiority of hybrids over their parents, is a major genetic force associated with plant fitness and crop yield enhancement. Understanding and predicting heterosis is crucial for evolutionary biology, as well as for plant and animal breeding. We investigated root-mediated yield heterosis in melons (Cucumis melo) by characterizing common variety grafted onto 190 hybrid rootstocks resulting from crossing 20 diverse inbreds in a diallel-mating scheme. Hybrid rootstocks improved yield by more than 40% compared to their parents and the best hybrid outperformed the reference commercial variety by 65% under both optimal and minimal irrigation treatments. To characterize the genetics of the underground heterosis we conducted whole-genome re-sequencing of the 20 founder lines, and showed that parental genetic distance was no predictor for the level of heterosis. Through inference of the 190 hybrids genotypes from their parental genomes, followed by genome-wide association analysis, we mapped multiple root-mediated yield QTLs. The yield enhancement of the four best-performing hybrid rootstocks was validated in multiple experiments with four different scion varieties. While root biology is receiving increased attention, most of the research is conducted using plants not amenable to grafting and, as a result, it is difficult to separate root and shoot effects. Here, we use the rich genetic and genomic resources of Cucumis melo, where grafting is a common practice, to dissect a unique phenomenon of root-mediated yield heterosis, by directly evaluating in the field the contribution of the roots to fruit yield. Our grafting approach is inverted to the common roots genetics research path that focuses mainly on variation in root system architecture rather than the ultimate root-mediated whole-plant performance, and is a step towards discovery of candidate genes involved in root function and yield enhancement. HighlightWe show that yield heterosis is significant in melon and controlled independently above and underground. Using common-scion grafting approach, we find that heritable rootstock-mediated variation in a diallel population is associated with substantial fruit yield heterosis.

plant biology↗

bioRxiv2021

Deconvolving clinically relevant cellular immune crosstalk from bulk gene expression using CODEFACS and LIRICS

The tumor microenvironment (TME) is a complex mixture of cell types whose interactions affect tumor growth and clinical outcome. To discover such interactions, we developed CODEFACS (COnfident DEconvolution For All Cell Subsets), a tool deconvolving cell-type-specific gene expression in each sample from bulk expression, and LIRICS (LIgand Receptor Interactions between Cell Subsets), a statistical framework prioritizing clinically relevant ligand-receptor interactions between cell types from the deconvolved data. We first demonstrate the superiority of CODEFACS versus the state-of-the-art deconvolution method, CIBERSORTx. Second, analyzing the TCGA, we uncover cell-type-specific interactions of mismatch-repair-deficient tumors that are associated with their higher anti-PD1 response rates, including specific T-cell co-stimulating interactions that enhance immunotherapy response independently of the tumors mutation burden levels. Finally, we identify a subset of ligand-receptor interactions in the melanoma TME that predict patient response to anti-PD1 therapy better than recently published transcriptomics-based methods.

bioinformatics↗

bioRxiv2020

PhISCS-BnB: A Fast Branch and Bound Algorithm for the Perfect Tumor Phylogeny Reconstruction Problem

MotivationRecent advances in single cell sequencing (SCS) offer an unprecedented insight into tumor emergence and evolution. Principled approaches to tumor phylogeny reconstruction via SCS data are typically based on general computational methods for solving an integer linear program (ILP), or a constraint satisfaction program (CSP), which, although guaranteeing convergence to the most likely solution, are very slow. Others based on Monte Carlo Markov Chain (MCMC) or alternative heuristics not only offer no such guarantee, but also are not faster in practice. As a result, novel methods that can scale up to handle the size and noise characteristics of emerging SCS data are highly desirable to fully utilize this technology. ResultsWe introduce PhISCS-BnB, a Branch and Bound algorithm to compute the most likely perfect phylogeny (PP) on an input genotype matrix extracted from a SCS data set. PhISCS-BnB not only offers an optimality guarantee, but is also 10 to 100 times faster than the best available methods on simulated tumor SCS data. We also applied PhISCS-BnB on a large melanoma data set derived from the sub-lineages of a cell line involving 24 clones with 3574 mutations, which returned the optimal tumor phylogeny in less than 2 hours. The resulting phylogeny also agrees with bulk exome sequencing data obtained from in vivo tumors growing out from the same cell line. Availabilityhttps://github.com/algo-cancer/PhISCS-BnB

bioinformatics↗

bioRxiv2020

The Landscape of Precision Cancer Combination Therapy: A Single-Cell Perspective

The availability of single-cell transcriptomics data opens new opportunities for rational design of combination cancer treatments. Mining such data, we employed combinatorial optimization techniques to explore the landscape of optimal combination therapies in solid tumors including brain, head and neck, melanoma, lung, breast and colon cancers. We assume that each individual therapy can target any one of 1269 genes encoding cell surface receptors, which may be targets of CAR-T, conjugated antibodies or coated nanoparticle therapies. As a baseline case, we studied the killing of at least 80% of the tumor cells while sparing more than 90% of the non-tumor cells in each patient, as a putative regimen. We find that in most cancer types, personalized combinations composed of at most four targets are then sufficient. However, the number of distinct targets that one would need to assemble to treat all patients in a cohort accordingly would be around 10 in most cases. Further requiring that the target genes be also lowly expressed in healthy tissues uncovers qualitatively similar trends. However, as one asks for more stringent and selective killing beyond the baseline regimen we focused on, we find that the number of targets needed rises rapidly. Emerging individual promising receptor targets include PTPRZ1, which is frequently found in the optimal combinations for brain and head and neck cancers, and EGFR, a recurring target in multiple tumor types. In sum, this systematic single-cell based characterization of the landscape of combinatorial receptor-mediated cancer treatments establishes first of their kind estimates on the number of targets needed, identifying promising ones for future development.

bioinformatics↗

bioRxiv2020

Melon ethylene-mediated transcriptome and methylome dynamics provide insights to volatile production

During climacteric ripening large-scale transcriptional modifications are governed by ethylene. While ripening-related chromatin modifications are also known to occur, a direct connection between these factors has not been demonstrated. We characterized ethylene-mediated transcriptome modification, genome methylation dynamics, and their relation to organoleptic modifications during fruit ripening in the climacteric melon and an ethylene repressed line where the fruit-specific ACC oxidase 1 (ACO1) gene was targeted by antisense. The ACO1 antisense line exhibited mainly reduced transcriptional repression of ripening-related genes associated with DNA CHH hypomethylation at the onset of ripening. Additionally, transcription of a small set of ethylene-induced genes, including known ripening-associated genes, was inhibited by ACO1 repression and this inhibition was associated with CG hypermethylation. In the ACO1 antisense line, the accumulation of aromatic compounds, which are mainly derived from the catabolism of amino acids, is known to be inhibited. One of the ethylene-mediated transcriptionally up-regulated genes, CmTHA1, encoding a threonine aldolase, exhibited differential cytosine methylation. Threonine aldolase catalyzes the conversion of L-threonine/L-allo threonine to glycine and acetaldehyde and thus is likely involved in threonine-dependent ethyl ester biosynthesis. Yeast mutant complementation and incubation of melon discs with labeled threonine verified CmTHA1 threonine aldolase activity, revealing an additional ethylene-dependent amino acid catabolism branch involved in climacteric melon ripening.

plant biology↗

bioRxiv2020

Ancestral Haplotype Reconstruction in Endogamous Populations using Identity-By-Descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs. We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to the United States from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 10 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct - we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families. Author summaryWhen analyzing complex heritable traits, it is often useful to have genomic data from many generations of an extended family, to increase the amount of information available for statistical inference. However, we typically only have genomic data from the recent generations of a pedigree, as ancestral individuals are deceased. In this work we present an algorithm, called thread, for reconstructing the genomes of ancestral individuals, given a complex pedigree and genomic data from the recent generations. Previous approaches have not been able to accommodate large datasets (both in terms of sites and individuals), made simplifying assumptions about pedigree structure, or did not tie reconstructed sequences back to specific individuals. We apply thread to a complex Old Order Amish pedigree of 1338 individuals, 394 with genotype data.

bioinformatics↗

bioRxiv2019

Multi-allelic APRR2 Gene is Associated with Fruit Pigment Accumulation in Melon and Watermelon

Color and pigment content are important aspects of fruit quality and consumer acceptance of cucurbit crops. Here, we describe the independent mapping and cloning of a common causative APRR2 gene regulating pigment accumulation in melon and watermelon. We initially show that the APRR2 transcription factor is causative for the qualitative difference between dark and light green rind in both crops. Further analyses establish the link between sequence or expression level variations in the CmAPRR2 gene and pigments content in the rind and flesh of mature melon fruits. GWAS of young fruit rind color in a panel composed of 177 diverse melon accessions did not result in any significant association, leading to an earlier assumption that multiple genes are involved in shaping the overall phenotypic variation at this trait. Through resequencing of 25 representative accessions and allelism tests between light rind accessions, we show that multiple independent SNPs in the CmAPRR2 gene are causative for the light rind phenotype. The multi-haplotypic nature of this gene explain the lack of detection power obtained through GBS-based GWAS and confirm the pivotal role of this gene in shaping fruit color variation in melon. This study demonstrates the power of combining bi- and multi-allelic designs with deep sequencing, to resolve lack of power due to high haplotypic diversity and low allele frequencies. Due to its central role and broad effect on pigment accumulation in fruits, the APRR2 gene is an attractive target for carotenoids bio-fortification of cucurbit crops.

plant biology↗