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Abstract As an invaluable Chinese sheep germplasm resource, Hu sheep are renowned for their high fertility and beautiful wavy lambskins. Their distinctive characteristics have evolved over time through a combination of artificial and natural selection. Identifying selection signatures in Hu sheep can provide a straightforward insight into the mechanism of selection and further uncover the candidate genes associated with breed‐specific traits subject to selection. Here, we conducted whole‐genome resequencing on 206 Hu sheep individuals, each with an approximate 6‐fold depth of coverage. And then we employed three complementary approaches, including composite likelihood ratio, integrated haplotype homozygosity score and the detection of runs of homozygosity, to detect selection signatures. In total, 10 candidate genomic regions displaying selection signatures were simultaneously identified by multiple methods, spanning 88.54 Mb. After annotating, these genomic regions harbored collectively 92 unique genes. Interestingly, 32 candidate genes associated with reproduction were distributed in nine genomic regions detected. Out of them, two stood out as star candidates: BMPR1B and GNRH2, both of which have documented associations with fertility, and a HOXA gene cluster (HOXA1‐5, HOXA9, HOXA10, HOXA11 and HOXA13) had also been linked to fertility. Additionally, we identified other genes that are related to hair follicle development (LAMTOR3, EEF1A2), ear size (HOXA1, KCNQ2), fat tail formation (HOXA10, HOXA11), growth and development (FAF1, CCNDBP1, GJB2, GJA3), fat deposition (ACOXL, JAZF1, HOXA3, HOXA4, HOXA5, EBF4), immune (UBR1, FASTKD5) and feed intake (DAPP1, RNF17, NPBWR2). Our results offer novel insights into the genetic mechanisms underlying the selection of breed‐specific traits in Hu sheep and provide a reference for sheep genetic improvement programs.

Abstract Repeat expansions are responsible for over 40 monogenic disorders, and undoubtedly more pathogenic repeat expansions remain to be discovered. Existing methods for detecting repeat expansions in short-read sequencing data require predefined repeat catalogs. Recent discoveries emphasize the need for methods that do not require pre-specified candidate repeats. To address this need, we introduce ExpansionHunter Denovo, an efficient catalog-free method for genome-wide repeat expansion detection. Analysis of real and simulated data shows that our method can identify large expansions of 41 out of 44 pathogenic repeats, including nine recently reported non-reference repeat expansions not discoverable via existing methods.