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CRII: III: RUI: Association Testing and Inversion Detection without Reference Genomes

CRII：III：RUI：无参考基因组的关联测试和倒置检测

基本信息

批准号：
1947257
负责人：
Ronald Nowling
金额：
$ 17.42万
依托单位：
Milwaukee School of Engineering
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-01 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1947257&HistoricalAwards=false
关键词：
CRII III RUI Association Testing

项目摘要

The last decade has seen the cost of DNA sequencing plummet. Consequently, the potential to sequence the genome of every living organism is within our grasp. Genome assemblies often require significant "polishing," which is often a manual and labor-intensive process. New methods are needed to directly analyze fragmented or unassembled genomic data. Analysis of these genomes include the identification of physical rearrangements such as inversions. Large inversions have significant impacts on the biology of organisms and their evolution. Existing computational methods for identifying inversions have been primarily tested on and developed for well-studied, "reference" genomes. This project seeks to develop new inversion detection and association testing methods suitable for the large and growing number of fragmented and/or unassembled genomes that are becoming available. Undergraduate research assistants will be funded as active collaborators on the project.So-called "k-mer" methods have become popular in the last decade for the analysis of unassembled genomics or metagenomics data. This project seeks to utilize k-mers, unsupervised learning, and association testing to identify inversions in fragmented or poorly assembled population genomics data. Since millions of association tests will be run per data set, the methods will be accelerated using GPUs. The resulting method and software will be developed in conjunction with undergraduate research assistants and released under an open-source license.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在过去的十年里，DNA测序的成本直线下降。因此，对每一个生物体的基因组进行测序的潜力就在我们的掌握之中。基因组组装通常需要大量的“抛光”，这通常是一个手工和劳动密集型的过程。需要新的方法来直接分析片段化或未组装的基因组数据。对这些基因组的分析包括鉴定物理重排，如倒位。大型倒位对生物的生物学及其进化具有重大影响。现有的用于识别倒位的计算方法主要是针对研究充分的“参考”基因组进行测试和开发的。该项目旨在开发新的倒位检测和关联检测方法，适用于大量和越来越多的碎片化和/或未组装的基因组。本科生研究助理将作为该项目的积极合作者获得资助。所谓的“k-mer”方法在过去十年中已经流行起来，用于分析未组装的基因组学或宏基因组学数据。该项目旨在利用k-mers，无监督学习和关联测试来识别碎片化或组装不良的群体基因组数据中的反转。由于每个数据集将运行数百万个关联测试，因此这些方法将使用GPU加速。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Prediction accuracy of regulatory elements from sequence varies by functional sequencing technique.

DOI：
10.3389/fcimb.2023.1182567
发表时间：
2023
期刊：
Frontiers in cellular and infection microbiology
影响因子：
5.7
作者：
通讯作者：

Comprehensive Genomic Discovery of Non-Coding Transcriptional Enhancers in the African Malaria Vector Anopheles coluzzii.

DOI：
10.3389/fgene.2021.785934
发表时间：
2021
期刊：
Frontiers in genetics
影响因子：
3.7
作者：
Holm I;Nardini L;Pain A;Bischoff E;Anderson CE;Zongo S;Guelbeogo WM;Sagnon N;Gohl DM;Nowling RJ;Vernick KD;Riehle MM
通讯作者：
Riehle MM

PeakMatcher: Matching Peaks Across Genome Assemblies

PeakMatcher：跨基因组组件匹配峰

DOI：
10.1145/3388440.3414907
发表时间：
2020
期刊：
Computational Biology and Health Informatics
影响因子：
0
作者：
Nowling, Ronald J.;Beal, Christopher R.;Emrich, Scott;Behura, Susanta K.;Halfon, Marc S.;Duman-Scheel, Molly
通讯作者：
Duman-Scheel, Molly

Segmenting and Genotyping Large, Polymorphic Inversions

大型多态性倒位的分割和基因分型

DOI：
10.1109/eit57321.2023.10187331
发表时间：
2023
期刊：
2023 IEEE International Conference on Electro Information Technology (eIT
影响因子：
0
作者：
Nowling, Ronald J.;Keyser, Samuel H.;Moran, Alex R.;Peters, John G.;Leskiewicz, Daniel
通讯作者：
Leskiewicz, Daniel

Filtering STARR-Seq Peaks for Enhancers with Sequence Models

使用序列模型过滤 STARR-Seq 峰以获取增强子