Journal of Genetics and Genomics

Improvement of wheat drought tolerance through editing of TaATX4 by CRISPR/Cas9

Zhongxue Wang, Yifang Zhang, et al.

doi: 10.1016/j.jgg.2023.10.001

Abstract (0) PDF (0)

Abstract:

Distinguished biological adaptation architecture aggravated population differentiation of Tibeto-Burman-speaking people inferred from 500 whole-genome data from 39 populations

Yuntao Sun, Mengge Wang, et al.

doi: 10.1016/j.jgg.2023.10.002

Abstract (26) PDF (6)

Abstract:
Tibeto-Burman (TB) people have endeavored to adapt to the hypoxic, cold, and high-UV high-altitude environments in the Tibetan Plateau and complex disease exposures in lowland rainforests since the late Paleolithic period. However, the full landscape of genetic history and biological adaptation of geographically diverse TB-speaking people, as well as their interaction mechanism remain unknown. We generate a whole-genome meta-database of 500 individuals from 39 TB-speaking populations in East Asia and Southeast Asia and present a comprehensive landscape of genetic diversity, admixture history, and differentiated adaptative features of geographically different TB-speaking people. We identify genetic differentiation related to geography and language among TB-speaking people, consistent with their differentiated admixture process with incoming or indigenous ancestral source populations. A robust genetic connection between the Tibetan-Yi corridor and ancient Yellow River people supports their Northern China origin hypothesis. We finally report substructure-related differentiated biological adaptative signatures between highland Tibetans and Loloish speakers. Adaptative signatures associated with the physical pigmentation (EDAR and SLC24A5) and metabolism (ALDH9A1) are identified in Loloish people, which differed from the high-altitude adaptative genetic architecture in Tibetan. TB-related genomic resources provide new insights into the genetic basis of biological adaptation and better reference for the anthropologically-informed sampling design in biomedical and genomic cohort research.

The genome-wide meiotic recombination landscape in ciliates and its implications for crossover regulation and genome evolution

Lu Fu, Chen Gu, et al.

doi: 10.1016/j.jgg.2023.09.013

Abstract (12) PDF (5)

Abstract:
Meiotic recombination is essential for sexual reproduction and its regulation has been extensively studied in many taxa. However, genome-wide recombination landscape has not been reported in ciliates and it remains unknown how it is affected by the unique features of ciliates: the synaptonemal complex (SC)-independent meiosis and the nuclear dimorphism. Here we show the recombination landscape in the model ciliate Tetrahymena thermophila by analyzing single-nucleotide polymorphism datasets from 38 hybrid progeny. We detect 1021 crossover (CO) events (35.8 per meiosis), corresponding to an overall CO rate of 9.9 cM/Mb. However, gene conversion by non-crossover is rare (1.03 per meiosis) and not biased toward G or C alleles. Consistent with the reported roles of SC in CO interference, we find no obvious sign of CO interference. CO tends to occur within germ-soma common genomic regions and many of the 44 identified CO hotspots localize at the centromeric or subtelomeric regions. Gene Ontology analyses show that CO hotspots are strongly associated with genes responding to environmental changes. We discuss these results with respect to how nuclear dimorphism has potentially driven the formation of the observed recombination landscape to facilitate environmental adaptation and the sharing of machinery among meiotic and somatic recombination.

Triticeae-BGC: a Web-based platform for detecting, annotating and evolutionary analysis of biosynthetic gene clusters in Triticeae

Mingxv Li, Haoyu Wang, et al.

doi: 10.1016/j.jgg.2023.09.014

Abstract (58) PDF (17)

Abstract:

IMAGGS: a radiogenomic framework for identifying multi-way associations in breast cancer subtypes

Shuyu Liang, Sicheng Xu, et al.

doi: 10.1016/j.jgg.2023.09.010

Abstract (16) PDF (2)

Abstract:

The investigation of correlations between radiomic and genomic profiling in breast cancer (BC) molecular subtypes is crucial for understanding disease mechanisms and providing personalized treatment. We present a well-designed radiogenomic framework—image-gene-gene set (IMAGGS), which detects multi-way associations in BC subtypes by integrating radiomic and genomic features.Our dataset consists of 721 patients, each of whom has 12 ultrasound (US) images captured from different angles and gene mutation data. To better characterize tumor traits, 12 multi-angle US images are fused using two distinct strategies. Then, we analyze complex many-to-many associations between phenotypic and genotypic features using a machine learning algorithm, deviating from the prevalent one-to-one relationship pattern observed in previous studies. Key radiomic and genomic features are screened using these associations. In addition, gene set enrichment analysis is performed to investigate the joint effects of gene sets and delve deeper into the biological functions of BC subtypes. We further validate the feasibility of IMAGGS in a glioblastoma multiforme dataset to demonstrate the scalability of IMAGGS across different modalities and diseases. Taken together, IMAGGS provides a comprehensive characterization for diseases by associating imaging, genes, and gene sets, paving the way for biological interpretation of radiomics and development of targeted therapy.

Unraveling the complexity of polycystic ovary syndrome with animal models

Huanju Liu, Mixue Tu, et al.

doi: 10.1016/j.jgg.2023.09.012

Abstract (21) PDF (3)

Abstract:

Polycystic ovary syndrome (PCOS) is a highly familial and heritable endocrine disorder. Over half of the daughters born to women with PCOS may eventually develop their own PCOS-related symptoms. Progress in the treatment of PCOS is currently hindered by the complexity of its clinical manifestations and incomplete knowledge of its etiopathogenesis. Various animal models, including experimentally-induced, naturally-occurring, and spontaneously-arising ones, have been established to emulate a wide range of phenotypical and pathological traits of human PCOS. These studies have led to a paradigm shift for understanding the genetic,developmental, and evolutionary origins of this disorder. Furthermore, emerging evidence suggests that animal models are useful in evaluating state-of-the-art drugs and treatments for PCOS. This review aims to provide a comprehensive summary of recent studies of PCOS in animal models, highlighting the power of these disease models in understanding the biology of PCOS and aiding high-throughput approaches.